PATENT DOCUMENT

Publication Number: US-11252299-B1
Application Number: US-202117176793-A
Country: US
Kind Code: B1

Title: High dynamic range color conversion using selective interpolation for different curves

Abstract:
Embodiments relate to pixel conversion of images for display. A circuit converts input pixel values of an image using a color conversion function. The circuit is operable in different modes where each mode uses a different color conversion function. A lookup table memory circuit stores a mapping of color converted values and input pixel values according to the mode of operation where the mapping represents the color conversion function associated with the mode. The circuit produces a color converted value from the lookup table as a color converted version of a first input pixel value responsive to the first input pixel value being within a first range. The circuit may also produce a color converted version of a second input pixel value by interpolating a subset of the color converted values received from the lookup table responsive to the second input pixel being within a second input range.

Claims:
What is claimed is: 
     
       1. A color conversion circuit, comprising:
 a mode register configured to store a mode value indicating a mode selected from a plurality of operation modes, each of the plurality of operation modes using a different color conversion function; 
 a lookup table memory circuit configured to store a mapping between color converted values and input pixel values as indicated by the selected operation mode; 
 a first fetcher circuit coupled to the lookup table memory circuit and configured to produce one of the color converted values received from the lookup table memory circuit as a color converted version of an input pixel value, responsive to the input pixel value being within a first input range of the color conversion function; and 
 an interpolator circuit coupled to the lookup table memory circuit and configured to produce the color converted version of the input pixel value by interpolating a subset of the color converted values received from the lookup table memory circuit, responsive to the input pixel value being within a second input range of the color conversion function, the second input range distinct from the first input range. 
 
     
     
       2. The color conversion circuit of  claim 1 , wherein a color conversion function in at least one of the plurality of operation modes is symmetric with respect to an axis or point, and wherein the lookup table memory circuit is configured to store the color converted values at one side of the axis or point but not store the color converted values at an opposite side of the axis or point. 
     
     
       3. The color conversion circuit of  claim 2 , wherein the first fetcher circuit is further configured to derive color converted values for input pixel values within the first input range of the color conversion function at the opposite side of the axis or point from the color converted values within the first input range of the color conversion function at the one side of the axis or the point that are stored in the lookup table memory circuit responsive to the selected mode representing the color conversion function that is symmetric with respect to the axis or point. 
     
     
       4. The color conversion circuit of  claim 3 , wherein the second fetcher circuit is further configured to derive color converted values for input pixel values within the second input range of the color conversion function at the opposite side of the axis or point from the color converted values within the second input range of the color conversion function at the one side of the axis or the point that are stored in the lookup table memory circuit responsive to the selected mode representing the color conversion function that is symmetric with respect to the axis or point. 
     
     
       5. The color conversion circuit of  claim 4 , further comprising a comparator circuit coupled to the first fetcher circuit and second fetcher circuit and configured to:
 determine whether the input pixel value is in the first input range or the second input range; 
 provide the input pixel value to the first fetcher circuit responsive to determining that the input pixel value is in the first input range; and 
 provide the input pixel value as the second input pixel value to the second fetcher circuit responsive to determining that the input pixel value is in the second input range. 
 
     
     
       6. The color correction circuit of  claim 1 , wherein a number of input pixel values and corresponding output pixel values in the first input range that are stored in the lookup table memory circuit is configurable to be either greater than or less than a number of input pixel values and corresponding output pixel values in the second input range that are stored in the lookup table memory circuit. 
     
     
       7. The color correction circuit of  claim 6 , wherein the second input range of the color conversion function includes a plurality of sub-input ranges, and a number of input pixel values and corresponding output pixel values stored in the lookup table memory circuit for each of the plurality of sub-input ranges is configurable. 
     
     
       8. The color correction circuit of  claim 7 , wherein the lookup table memory circuit stores a different number of input pixel values and corresponding output pixel values for at least two of the plurality of sub-input ranges. 
     
     
       9. The color correction circuit of  claim 1 , wherein responsive to a last point in the color conversion function having an index value in the lookup table memory circuit that is not a power of two, a configurable point is enabled such that the configurable point is the last point in the lookup table memory circuit for the color conversion function and has an index value that is a power of two in the lookup table memory circuit. 
     
     
       10. The color correction circuit of  claim 9 , wherein the lookup table memory circuit stores a same number of input pixel values and corresponding output pixel values for at least two of the plurality of sub-input ranges. 
     
     
       11. A method for pixel conversion of a color correction circuit, comprising:
 storing a mode value indicating a mode selected from a plurality of operation modes in a mode register of the color correction circuit, each of the plurality of operation modes using a different color conversion function; 
 storing a mapping between color converted values and input pixel values in a lookup table memory circuit as indicated by the selected operation mode; 
 producing one of the color converted values received from the lookup table memory circuit as a color converted version of an input pixel value, responsive to the input pixel value being within a first input range of the color conversion function; and 
 producing the color converted version of the input pixel value by interpolating a subset of the color converted values received from the lookup table memory circuit, 
 responsive to the input pixel value being within a second input range of the color conversion function, the second input range distinct from the first input range. 
 
     
     
       12. The method of  claim 11 , wherein a color conversion function in at least one of the plurality of operation modes is symmetric with respect to an axis or point, and the color converted values at one side of the axis or point is stored in the lookup table memory circuit but the color converted values at an opposite side of the axis or point is not stored in the lookup table memory circuit. 
     
     
       13. The method of  claim 12 , further comprising:
 deriving color converted values for input pixel values within the first input range of the color conversion function at the opposite side of the axis or point from the color converted values within the first input range of the color conversion function at the one side of the axis or the point that are stored in the lookup table memory circuit responsive to the selected mode representing the color conversion function that is symmetric with respect to the axis or point. 
 
     
     
       14. The method of  claim 13 , further comprising:
 deriving color converted values for input pixel values within the second input range of the color conversion function at the opposite side of the axis or point from the color converted values within the second input range of the color conversion function at the one side of the axis or the point that are stored in the lookup table memory circuit responsive to the selected mode representing the color conversion function that is symmetric with respect to the axis or point. 
 
     
     
       15. The method of  claim 11 , wherein a number of input pixel values and corresponding output pixel values in the first input range that are stored in the lookup table memory circuit is configurable to be either greater than or less than a number of input pixel values and corresponding output pixel values in the second input range that are stored in the lookup table memory circuit. 
     
     
       16. The method of  claim 15 , wherein the second input range of the color conversion function includes a plurality of sub-input ranges, and a number of input pixel values and corresponding output pixel values stored in the lookup table memory circuit for each of the plurality of sub-input ranges is configurable. 
     
     
       17. The method of  claim 16 , wherein a different number of input pixel values and corresponding output pixel values for at least two of the plurality of sub-input ranges are stored in the lookup table memory circuit. 
     
     
       18. The method of  claim 16 , wherein a same number of input pixel values and corresponding output pixel values for at least two of the plurality of sub-input ranges are stored in the lookup table memory circuit. 
     
     
       19. The method of  claim 11 , further comprising:
 responsive to a last point in the color conversion function having an index value in the lookup table memory circuit that is not a power of two, enabling a configurable point such that the configurable point is the last point in the lookup table memory circuit for the color conversion function and has an index value that is a power of two in the lookup table memory circuit. 
 
     
     
       20. A system for pixel conversion, comprising:
 an image sensor configured to obtain an image; and 
 an image signal processor coupled to the image sensor, the image signal processor configured to perform processing of the image, the image signal processor including:
 a mode register configured to store a mode value indicating a mode selected from a plurality of operation modes, each of the plurality of operation modes using a different color conversion function; 
 a lookup table memory circuit configured to store a mapping between color converted values and input pixel values as indicated by the selected operation mode; 
 a first fetcher circuit coupled to the lookup table memory circuit and configured to produce one of the color converted values received from the lookup table memory circuit as a color converted version of an input pixel value, responsive to the input pixel value being within a first input range of the color conversion function; and 
 an interpolator circuit coupled to the lookup table memory circuit and configured to produce the color converted version of the input pixel value by interpolating a subset of the color converted values received from the lookup table memory circuit, responsive to the input pixel value being within a second input range of the color conversion function, the second input range distinct from the first input range.

Description:
BACKGROUND 
     1. Field of the Disclosure 
     The present disclosure relates a circuit for processing images and more specifically to color conversion using non-linear mapping. 
     2. Description of the Related Arts 
     Image data captured by an image sensor or received from other data sources is often processed in an image processing pipeline before further processing or consumption. For example, raw image data may be corrected, filtered, or otherwise modified before being provided to subsequent components such as a video encoder. To perform corrections or enhancements for captured image data, various components, unit stages or modules may be employed. 
     Such an image processing pipeline may be structured so that corrections or enhancements to the captured image data can be performed in an expedient way without consuming other system resources. Although many image processing algorithms may be performed by executing software programs on central processing unit (CPU), execution of such programs on the CPU would consume significant bandwidth of the CPU and other peripheral resources as well as increase power consumption. Hence, image processing pipelines are often implemented as a hardware component separate from the CPU and dedicated to perform one or more image processing algorithms. 
     One of such operations performed by the image processing pipeline is conversion of image data in one format to HDR. To convert to HDR format, a color conversion function may be used to convert pixel data to a particular brightness. 
     SUMMARY 
     Embodiments relate to circuitry for converting input image pixel values of images into output image pixel values using a color conversion function. A circuit may operate in different operation modes where each operation mode uses a different color conversion function for color conversion of input image pixel values to output image pixel values. The color conversion function is divided into two regions with a first region including first input pixel conversion values and corresponding first output pixel conversion values, and a second region including second input pixel conversion values and corresponding second output pixel conversion values. The circuitry may convert an input image pixel value in the first region by fetching from a lookup table an output pixel conversion value indexed to the first input image pixel value in the lookup table and apply the fetched output pixel conversion value to the input image pixel value. In contrast, the circuitry performs linear interpolation to calculate a converted output image pixel value for an input image pixel value in the second region. Using the lookup table or linear interpolation to perform color conversion dependent on whether the input image pixel value is in the first region or second region preserves high precision of accuracy while reducing power consumption. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         FIG. 1  is a high-level diagram of an electronic device, according to one embodiment 
         FIG. 2  is a block diagram illustrating components in the electronic device, according to one embodiment. 
         FIG. 3  is a block diagram illustrating image processing pipelines implemented using an image signal processor, according to one embodiment. 
         FIG. 4  is a block diagram of a high dynamic range (HDR) color space converter, according to one embodiment. 
         FIG. 5  is a detailed block diagram of an HDR circuit, according to one embodiment. 
         FIGS. 6A, 6B, and 6C  are diagrams of a first type of color conversion function, according to one embodiment. 
         FIGS. 7A and 7B  are diagrams of a second type of color conversion function, according to one embodiment. 
         FIGS. 8A and 8B  are diagrams of a third type of color conversion function, according to one embodiment. 
         FIGS. 9A and 9B  are diagrams of a fourth type of color conversion function, according to one embodiment. 
         FIG. 10  is detailed block diagram of a color space converter included in the HDR circuit, according to one embodiment. 
         FIG. 11  is a flowchart illustrating a method of converting pixel values using a color conversion function, according to one embodiment. 
     
    
    
     The figures depict, and the detail description describes, various non-limiting embodiments for purposes of illustration only. 
     DETAILED DESCRIPTION 
     Reference will now be made in detail to embodiments, examples of which are illustrated in the accompanying drawings. In the following detailed description, numerous specific details are set forth in order to provide a thorough understanding of the various described embodiments. However, the described embodiments may be practiced without these specific details. In other instances, well-known methods, procedures, components, circuits, and networks have not been described in detail so as not to unnecessarily obscure aspects of the embodiments. 
     Embodiments of the present disclosure relate to a circuit for converting input image pixel values into output image pixel values of high dynamic range (HDR) format using a color conversion function. The circuit operates in at least two operation modes where each operation mode uses a different color conversion function to perform HDR color conversion. A look-up table is configurable to store values corresponding to the selected color conversion function. In a first region of the color conversion function, the look-up table may index different color components of each pixel. But in the second region of the color conversion function, the look-up table stores output pixel conversion values for only a portion of all possible input pixel conversion values in the second region of the color conversion function rather than for all possible input pixel conversion values in the second region. The circuit can calculate a converted output image pixel value for an input pixel image value in the second region using linear interpolation. In this way, more accurate color converted values can be obtained in the first region while providing reasonably accurate color converted values in the second region without significantly increasing memory of the circuit. 
     Exemplary Electronic Device 
     Embodiments of electronic devices, user interfaces for such devices, and associated processes for using such devices are described. In some embodiments, the device is a portable communications device, such as a mobile telephone, that also contains other functions, such as personal digital assistant (PDA) and/or music player functions. Exemplary embodiments of portable multifunction devices include, without limitation, the iPhone®, iPod Touch®, Apple Watch®, and iPad® devices from Apple Inc. of Cupertino, Calif. Other portable electronic devices, such as wearables, laptops or tablet computers, are optionally used. In some embodiments, the device is not a portable communications device, but is a desktop computer or other computing device that is not designed for portable use. In some embodiments, the disclosed electronic device may include a touch sensitive surface (e.g., a touch screen display and/or a touch pad). An example electronic device described below in conjunction with  FIG. 1  (e.g., device  100 ) may include a touch-sensitive surface for receiving user input. The electronic device may also include one or more other physical user-interface devices, such as a physical keyboard, a mouse and/or a joystick. 
     Figure ( FIG. 1  is a high-level diagram of an electronic device  100 , according to one embodiment. Device  100  may include one or more physical buttons, such as a “home” or menu button  104 . Menu button  104  is, for example, used to navigate to any application in a set of applications that are executed on device  100 . In some embodiments, menu button  104  includes a fingerprint sensor that identifies a fingerprint on menu button  104 . The fingerprint sensor may be used to determine whether a finger on menu button  104  has a fingerprint that matches a fingerprint stored for unlocking device  100 . Alternatively, in some embodiments, menu button  104  is implemented as a soft key in a graphical user interface (GUI) displayed on a touch screen. 
     In some embodiments, device  100  includes touch screen  150 , menu button  104 , push button  106  for powering the device on/off and locking the device, volume adjustment buttons  108 , Subscriber Identity Module (SIM) card slot  110 , head set jack  112 , and docking/charging external port  124 . Push button  106  may be used to turn the power on/off on the device by depressing the button and holding the button in the depressed state for a predefined time interval; to lock the device by depressing the button and releasing the button before the predefined time interval has elapsed; and/or to unlock the device or initiate an unlock process. In an alternative embodiment, device  100  also accepts verbal input for activation or deactivation of some functions through microphone  113 . The device  100  includes various components including, but not limited to, a memory (which may include one or more computer readable storage mediums), a memory controller, one or more central processing units (CPUs), a peripherals interface, an RF circuitry, an audio circuitry, speaker  111 , microphone  113 , input/output (I/O) subsystem, and other input or control devices. Device  100  may include one or more image sensors  164 , one or more proximity sensors  166 , and one or more accelerometers  168 . Device  100  may include more than one type of image sensors  164 . Each type may include more than one image sensor  164 . For example, one type of image sensors  164  may be cameras and another type of image sensors  164  may be infrared sensors that may be used for face recognition. In addition or alternatively, the image sensors  164  may be associated with different lens configuration. For example, device  100  may include rear image sensors, one with a wide-angle lens and another with as a telephoto lens. The device  100  may include components not shown in  FIG. 1  such as an ambient light sensor, a dot projector and a flood illuminator. 
     Device  100  is only one example of an electronic device, and device  100  may have more or fewer components than listed above, some of which may be combined into a component or have a different configuration or arrangement. The various components of device  100  listed above are embodied in hardware, software, firmware or a combination thereof, including one or more signal processing and/or application specific integrated circuits (ASICs). While the components in  FIG. 1  are shown as generally located on the same side as the touch screen  150 , one or more components may also be located on an opposite side of device  100 . For example, the front side of device  100  may include an infrared image sensor  164  for face recognition and another image sensor  164  as the front camera of device  100 . The back side of device  100  may also include additional two image sensors  164  as the rear cameras of device  100 . 
       FIG. 2  is a block diagram illustrating components in device  100 , according to one embodiment. Device  100  may perform various operations including image processing. For this and other purposes, the device  100  may include, among other components, image sensor  202 , system-on-a chip (SOC) component  204 , system memory  230 , persistent storage (e.g., flash memory)  228 , orientation sensor  234 , and display  216 . The components as illustrated in  FIG. 2  are merely illustrative. For example, device  100  may include other components (such as speaker or microphone) that are not illustrated in  FIG. 2 . Further, some components (such as orientation sensor  234 ) may be omitted from device  100 . 
     Image sensors  202  are components for capturing image data. Each of the image sensors  202  may be embodied, for example, as a complementary metal-oxide-semiconductor (CMOS) active-pixel sensor, a camera, video camera, or other devices. Image sensors  202  generate raw image data that is sent to SOC component  204  for further processing. In some embodiments, the image data processed by SOC component  204  is displayed on display  216 , stored in system memory  230 , persistent storage  228  or sent to a remote computing device via network connection. The raw image data generated by image sensors  202  may be in a Bayer color filter array (CFA) pattern (hereinafter also referred to as “Bayer pattern”). An image sensor  202  may also include optical and mechanical components that assist image sensing components (e.g., pixels) to capture images. The optical and mechanical components may include an aperture, a lens system, and an actuator that controls the lens position of the image sensor  202 . 
     Motion sensor  234  is a component or a set of components for sensing motion of device  100 . Motion sensor  234  may generate sensor signals indicative of orientation and/or acceleration of device  100 . The sensor signals are sent to SOC component  204  for various operations such as turning on device  100  or rotating images displayed on display  216 . 
     Display  216  is a component for displaying images as generated by SOC component  204 . Display  216  may include, for example, liquid crystal display (LCD) device or an organic light emitting diode (OLED) device. Based on data received from SOC component  204 , display  116  may display various images, such as menus, selected operating parameters, images captured by image sensor  202  and processed by SOC component  204 , and/or other information received from a user interface of device  100  (not shown). 
     System memory  230  is a component for storing instructions for execution by SOC component  204  and for storing data processed by SOC component  204 . System memory  230  may be embodied as any type of memory including, for example, dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate (DDR, DDR2, DDR3, etc.) RAMBUS DRAM (RDRAM), static RAM (SRAM) or a combination thereof. In some embodiments, system memory  230  may store pixel data or other image data or statistics in various formats. 
     Persistent storage  228  is a component for storing data in a non-volatile manner. Persistent storage  228  retains data even when power is not available. Persistent storage  228  may be embodied as read-only memory (ROM), flash memory or other non-volatile random access memory devices. 
     SOC component  204  is embodied as one or more integrated circuit (IC) chip and performs various data processing processes. SOC component  204  may include, among other subcomponents, image signal processor (ISP)  206 , a central processor unit (CPU)  208 , a network interface  210 , motion sensor interface  212 , display controller  214 , graphics processor (GPU)  220 , memory controller  222 , video encoder  224 , storage controller  226 , and various other input/output (I/O) interfaces  218 , and bus  232  connecting these subcomponents. SOC component  204  may include more or fewer subcomponents than those shown in  FIG. 2 . 
     ISP  206  is hardware that performs various stages of an image processing pipeline. In some embodiments, ISP  206  may receive raw image data from image sensor  202 , and process the raw image data into a form that is usable by other subcomponents of SOC component  204  or components of device  100 . ISP  206  may perform various image-manipulation operations such as image translation operations, horizontal and vertical scaling, color space conversion and/or image stabilization transformations, as described below in detail with reference to  FIG. 3 . 
     CPU  208  may be embodied using any suitable instruction set architecture, and may be configured to execute instructions defined in that instruction set architecture. CPU  208  may be general-purpose or embedded processors using any of a variety of instruction set architectures (ISAs), such as the x86, PowerPC, SPARC, RISC, ARM or MIPS ISAs, or any other suitable ISA. Although a single CPU is illustrated in  FIG. 2 , SOC component  204  may include multiple CPUs. In multiprocessor systems, each of the CPUs may commonly, but not necessarily, implement the same ISA. 
     Graphics processing unit (GPU)  220  is graphics processing circuitry for performing graphical data. For example, GPU  220  may render objects to be displayed into a frame buffer (e.g., one that includes pixel data for an entire frame). GPU  220  may include one or more graphics processors that may execute graphics software to perform a part or all of the graphics operation, or hardware acceleration of certain graphics operations. 
     I/O interfaces  218  are hardware, software, firmware or combinations thereof for interfacing with various input/output components in device  100 . I/O components may include devices such as keypads, buttons, audio devices, and sensors such as a global positioning system. I/O interfaces  218  process data for sending data to such I/O components or process data received from such I/O components. 
     Network interface  210  is a subcomponent that enables data to be exchanged between devices  100  and other devices via one or more networks (e.g., carrier or agent devices). For example, video or other image data may be received from other devices via network interface  210  and be stored in system memory  230  for subsequent processing (e.g., via a back-end interface to image signal processor  206 , such as discussed below in  FIG. 3 ) and display. The networks may include, but are not limited to, Local Area Networks (LANs) (e.g., an Ethernet or corporate network) and Wide Area Networks (WANs). The image data received via network interface  210  may undergo image processing processes by ISP  206 . 
     Motion sensor interface  212  is circuitry for interfacing with motion sensor  234 . Motion sensor interface  212  receives sensor information from motion sensor  234  and processes the sensor information to determine the orientation or movement of the device  100 . 
     Display controller  214  is circuitry for sending image data to be displayed on display  216 . Display controller  214  receives the image data from ISP  206 , CPU  208 , graphic processor or system memory  230  and processes the image data into a format suitable for display on display  216 . 
     Memory controller  222  is circuitry for communicating with system memory  230 . Memory controller  222  may read data from system memory  230  for processing by ISP  206 , CPU  208 , GPU  220  or other subcomponents of SOC component  204 . Memory controller  222  may also write data to system memory  230  received from various subcomponents of SOC component  204 . 
     Video encoder  224  is hardware, software, firmware or a combination thereof for encoding video data into a format suitable for storing in persistent storage  128  or for passing the data to network interface w10 for transmission over a network to another device. 
     In some embodiments, one or more subcomponents of SOC component  204  or some functionality of these subcomponents may be performed by software components executed on ISP  206 , CPU  208  or GPU  220 . Such software components may be stored in system memory  230 , persistent storage  228  or another device communicating with device  100  via network interface  210 . 
     Image data or video data may flow through various data paths within SOC component  204 . In one example, raw image data may be generated from the image sensors  202  and processed by ISP  206 , and then sent to system memory  230  via bus  232  and memory controller  222 . After the image data is stored in system memory  230 , it may be accessed by video encoder  224  for encoding or by display  116  for displaying via bus  232 . 
     In another example, image data is received from sources other than the image sensors  202 . For example, video data may be streamed, downloaded, or otherwise communicated to the SOC component  204  via wired or wireless network. The image data may be received via network interface  210  and written to system memory  230  via memory controller  222 . The image data may then be obtained by ISP  206  from system memory  230  and processed through one or more image processing pipeline stages, as described below in detail with reference to  FIG. 3 . The image data may then be returned to system memory  230  or be sent to video encoder  224 , display controller  214  (for display on display  216 ), or storage controller  226  for storage at persistent storage  228 . 
     Example Image Signal Processing Pipelines 
       FIG. 3  is a block diagram illustrating image processing pipelines implemented using ISP  206 , according to one embodiment. In the embodiment of  FIG. 3 , ISP  206  is coupled to an image sensor system  201  that includes one or more image sensors  202 A through  202 N (hereinafter collectively referred to as “image sensors  202 ” or also referred individually as “image sensor  202 ”) to receive raw image data. The image sensor system  201  may include one or more sub-systems that control the image sensors  202  individually. In some cases, each image sensor  202  may operate independently while, in other cases, the image sensors  202  may share some components. For example, in one embodiment, two or more image sensors  202  may be share the same circuit board that controls the mechanical components of the image sensors (e.g., actuators that change the lens positions of each image sensor). The image sensing components of an image sensor  202  may include different types of image sensing components that may provide raw image data in different forms to the ISP  206 . For example, in one embodiment, the image sensing components may include a plurality of focus pixels that are used for auto-focusing and a plurality of image pixels that are used for capturing images. In another embodiment, the image sensing pixels may be used for both auto-focusing and image capturing purposes. 
     ISP  206  implements an image processing pipeline which may include a set of stages that process image information from creation, capture or receipt to output. ISP  206  may include, among other components, sensor interface  302 , central control  320 , front-end pipeline stages  330 , back-end pipeline stages  340 , image statistics module  304 , vision module  322 , back-end interface  342 , output interface  316 , and auto-focus circuits  350 A through  350 N (hereinafter collectively referred to as “auto-focus circuits  350 ” or referred individually as “auto-focus circuits  350 ”). ISP  206  may include other components not illustrated in  FIG. 3  or may omit one or more components illustrated in  FIG. 3 . 
     In one or more embodiments, different components of ISP  206  process image data at different rates. In the embodiment of  FIG. 3 , front-end pipeline stages  330  (e.g., raw processing stage  306  and resample processing stage  308 ) may process image data at an initial rate. Thus, the various different techniques, adjustments, modifications, or other processing operations performed by these front-end pipeline stages  330  at the initial rate. For example, if the front-end pipeline stages  330  process 2 pixels per clock cycle, then raw processing stage  306  operations (e.g., black level compensation, highlight recovery and defective pixel correction) may process 2 pixels of image data at a time. In contrast, one or more back-end pipeline stages  340  may process image data at a different rate less than the initial data rate. For example, in the embodiment of  FIG. 3 , back-end pipeline stages  340  (e.g., noise processing stage  310 , color processing stage  312 , and output rescale  314 ) may be processed at a reduced rate (e.g., 1 pixel per clock cycle). 
     Raw image data captured by image sensors  202  may be transmitted to different components of ISP  206  in different manners. In one embodiment, raw image data corresponding to the focus pixels may be sent to the auto-focus circuits  350  while raw image data corresponding to the image pixels may be sent to the sensor interface  302 . In another embodiment, raw image data corresponding to both types of pixels may simultaneously be sent to both the auto-focus circuits  350  and the sensor interface  302 . 
     Auto-focus circuits  350  may include hardware circuit that analyzes raw image data to determine an appropriate lens position of each image sensor  202 . In one embodiment, the raw image data may include data that is transmitted from image sensing pixels that specializes in image focusing. In another embodiment, raw image data from image capture pixels may also be used for auto-focusing purpose. An auto-focus circuit  350  may perform various image processing operations to generate data that determines the appropriate lens position. The image processing operations may include cropping, binning, image compensation, scaling to generate data that is used for auto-focusing purpose. The auto-focusing data generated by auto-focus circuits  350  may be fed back to the image sensor system  201  to control the lens positions of the image sensors  202 . For example, an image sensor  202  may include a control circuit that analyzes the auto-focusing data to determine a command signal that is sent to an actuator associated with the lens system of the image sensor to change the lens position of the image sensor. The data generated by the auto-focus circuits  350  may also be sent to other components of the ISP  206  for other image processing purposes. For example, some of the data may be sent to image statistics  304  to determine information regarding auto-exposure. 
     The auto-focus circuits  350  may be individual circuits that are separate from other components such as image statistics  304 , sensor interface  302 , front-end  330  and back-end  340 . This allows the ISP  206  to perform auto-focusing analysis independent of other image processing pipelines. For example, the ISP  206  may analyze raw image data from the image sensor  202 A to adjust the lens position of image sensor  202 A using the auto-focus circuit  350 A while performing downstream image processing of the image data from image sensor  202 B simultaneously. In one embodiment, the number of auto-focus circuits  350  may correspond to the number of image sensors  202 . In other words, each image sensor  202  may have a corresponding auto-focus circuit that is dedicated to the auto-focusing of the image sensor  202 . The device  100  may perform auto focusing for different image sensors  202  even if one or more image sensors  202  are not in active use. This allows a seamless transition between two image sensors  202  when the device  100  switches from one image sensor  202  to another. For example, in one embodiment, a device  100  may include a wide-angle camera and a telephoto camera as a dual back camera system for photo and image processing. The device  100  may display images captured by one of the dual cameras and may switch between the two cameras from time to time. The displayed images may seamless transition from image data captured by one image sensor  202  to image data captured by another image sensor without waiting for the second image sensor  202  to adjust its lens position because two or more auto-focus circuits  350  may continuously provide auto-focus data to the image sensor system  201 . 
     Raw image data captured by different image sensors  202  may also be transmitted to sensor interface  302 . Sensor interface  302  receives raw image data from image sensor  202  and processes the raw image data into an image data processable by other stages in the pipeline. Sensor interface  302  may perform various preprocessing operations, such as image cropping, binning or scaling to reduce image data size. In some embodiments, pixels are sent from the image sensor  202  to sensor interface  302  in raster order (e.g., horizontally, line by line). The subsequent processes in the pipeline may also be performed in raster order and the result may also be output in raster order. Although only a single image sensor and a single sensor interface  302  are illustrated in  FIG. 3 , when more than one image sensor is provided in device  100 , a corresponding number of sensor interfaces may be provided in ISP  206  to process raw image data from each image sensor. 
     Front-end pipeline stages  330  process image data in raw or full-color domains. Front-end pipeline stages  330  may include, but are not limited to, raw processing stage  306  and resample processing stage  308 . A raw image data may be in Bayer raw format, for example. In Bayer raw image format, pixel data with values specific to a particular color (instead of all colors) is provided in each pixel. In an image capturing sensor, image data is typically provided in a Bayer pattern. Raw processing stage  306  may process image data in a Bayer raw format. 
     The operations performed by raw processing stage  306  include, but are not limited, sensor linearization, black level compensation, fixed pattern noise reduction, defective pixel correction, raw noise filtering, lens shading correction, white balance gain, and highlight recovery. Sensor linearization refers to mapping non-linear image data to linear space for other processing. Black level compensation refers to providing digital gain, offset and clip independently for each color component (e.g., Gr, R, B, Gb) of the image data. Fixed pattern noise reduction refers to removing offset fixed pattern noise and gain fixed pattern noise by subtracting a dark frame from an input image and multiplying different gains to pixels. Defective pixel correction refers to detecting defective pixels, and then replacing defective pixel values. Raw noise filtering refers to reducing noise of image data by averaging neighbor pixels that are similar in brightness. Highlight recovery refers to estimating pixel values for those pixels that are clipped (or nearly clipped) from other channels. Lens shading correction refers to applying a gain per pixel to compensate for a dropoff in intensity roughly proportional to a distance from a lens optical center. White balance gain refers to providing digital gains for white balance, offset and clip independently for all color components (e.g., Gr, R, B, Gb in Bayer format). Components of ISP  206  may convert raw image data into image data in full-color domain, and thus, raw processing stage  306  may process image data in the full-color domain in addition to or instead of raw image data. 
     Resample processing stage  308  performs various operations to convert, resample, or scale image data received from raw processing stage  306 . Operations performed by resample processing stage  308  may include, but not limited to, demosaic operation, per-pixel color correction operation, Gamma mapping operation, color space conversion and downscaling or sub-band splitting. Demosaic operation refers to converting or interpolating missing color samples from raw image data (for example, in a Bayer pattern) to output image data into a full-color domain. Demosaic operation may include low pass directional filtering on the interpolated samples to obtain full-color pixels. Per-pixel color correction operation refers to a process of performing color correction on a per-pixel basis using information about relative noise standard deviations of each color channel to correct color without amplifying noise in the image data. Gamma mapping refers to converting image data from input image data values to output data values to perform gamma correction. For the purpose of Gamma mapping, lookup tables (or other structures that index pixel values to another value) for different color components or channels of each pixel (e.g., a separate lookup table for R, G, and B color components) may be used. Color space conversion refers to converting color space of an input image data into a different format. In one embodiment, resample processing stage  308  converts RGB format into YCbCr format for further processing. 
     Central control module  320  may control and coordinate overall operation of other components in ISP  206 . Central control module  320  performs operations including, but not limited to, monitoring various operating parameters (e.g., logging clock cycles, memory latency, quality of service, and state information), updating or managing control parameters for other components of ISP  206 , and interfacing with sensor interface  302  to control the starting and stopping of other components of ISP  206 . For example, central control module  320  may update programmable parameters for other components in ISP  206  while the other components are in an idle state. After updating the programmable parameters, central control module  320  may place these components of ISP  206  into a run state to perform one or more operations or tasks. Central control module  320  may also instruct other components of ISP  206  to store image data (e.g., by writing to system memory  230  in  FIG. 2 ) before, during, or after resample processing stage  308 . In this way full-resolution image data in raw or full-color domain format may be stored in addition to or instead of processing the image data output from resample processing stage  308  through backend pipeline stages  340 . 
     Image statistics module  304  performs various operations to collect statistic information associated with the image data. The operations for collecting statistics information may include, but not limited to, sensor linearization, replace patterned defective pixels, sub-sample raw image data, detect and replace non-patterned defective pixels, black level compensation, lens shading correction, and inverse black level compensation. After performing one or more of such operations, statistics information such as  3 A statistics (Auto white balance (AWB), auto exposure (AE), histograms (e.g., 2D color or component) and any other image data information may be collected or tracked. In some embodiments, certain pixels&#39; values, or areas of pixel values may be excluded from collections of certain statistics data when preceding operations identify clipped pixels. Although only a single statistics module  304  is illustrated in  FIG. 3 , multiple image statistics modules may be included in ISP  206 . For example, each image sensor  202  may correspond to an individual image statistics unit  304 . In such embodiments, each statistic module may be programmed by central control module  320  to collect different information for the same or different image data. 
     Vision module  322  performs various operations to facilitate computer vision operations at CPU  208  such as facial detection in image data. The vision module  322  may perform various operations including pre-processing, global tone-mapping and Gamma correction, vision noise filtering, resizing, keypoint detection, generation of histogram-of-orientation gradients (HOG) and normalized cross correlation (NCC). The pre-processing may include subsampling or binning operation and computation of luminance if the input image data is not in YCrCb format. Global mapping and Gamma correction can be performed on the pre-processed data on luminance image. Vision noise filtering is performed to remove pixel defects and reduce noise present in the image data, and thereby, improve the quality and performance of subsequent computer vision algorithms. Such vision noise filtering may include detecting and fixing dots or defective pixels, and performing bilateral filtering to reduce noise by averaging neighbor pixels of similar brightness. Various vision algorithms use images of different sizes and scales. Resizing of an image is performed, for example, by binning or linear interpolation operation. Keypoints are locations within an image that are surrounded by image patches well suited to matching in other images of the same scene or object. Such keypoints are useful in image alignment, computing camera pose and object tracking. Keypoint detection refers to the process of identifying such keypoints in an image. HOG provides descriptions of image patches for tasks in mage analysis and computer vision. HOG can be generated, for example, by (i) computing horizontal and vertical gradients using a simple difference filter, (ii) computing gradient orientations and magnitudes from the horizontal and vertical gradients, and (iii) binning the gradient orientations. NCC is the process of computing spatial cross-correlation between a patch of image and a kernel. 
     Back-end interface  342  receives image data from other image sources than image sensor  102  and forwards it to other components of ISP  206  for processing. For example, image data may be received over a network connection and be stored in system memory  230 . Back-end interface  342  retrieves the image data stored in system memory  230  and provides it to back-end pipeline stages  340  for processing. One of many operations that are performed by back-end interface  342  is converting the retrieved image data to a format that can be utilized by back-end processing stages  340 . For instance, back-end interface  342  may convert RGB, YCbCr 4:2:0, or YCbCr 4:2:2 formatted image data into YCbCr 4:4:4 color format. 
     Back-end pipeline stages  340  processes image data according to a particular full-color format (e.g., YCbCr 4:4:4 or RGB). In some embodiments, components of the back-end pipeline stages  340  may convert image data to a particular full-color format before further processing. Back-end pipeline stages  340  may include, among other stages, noise processing stage  310  and color processing stage  312 . Back-end pipeline stages  340  may include other stages not illustrated in  FIG. 3 . 
     Noise processing stage  310  performs various operations to reduce noise in the image data. The operations performed by noise processing stage  310  include, but are not limited to, color space conversion, gamma/de-gamma mapping, temporal filtering, noise filtering, luma sharpening, and chroma noise reduction. The color space conversion may convert an image data from one color space format to another color space format (e.g., RGB format converted to YCbCr format). Gamma/de-gamma operation converts image data from input image data values to output data values to perform gamma correction or reverse gamma correction. Temporal filtering filters noise using a previously filtered image frame to reduce noise. For example, pixel values of a prior image frame are combined with pixel values of a current image frame. Noise filtering may include, for example, spatial noise filtering. Luma sharpening may sharpen luma values of pixel data while chroma suppression may attenuate chroma to gray (e.g. no color). In some embodiment, the luma sharpening and chroma suppression may be performed simultaneously with spatial nose filtering. The aggressiveness of noise filtering may be determined differently for different regions of an image. Spatial noise filtering may be included as part of a temporal loop implementing temporal filtering. For example, a previous image frame may be processed by a temporal filter and a spatial noise filter before being stored as a reference frame for a next image frame to be processed. In other embodiments, spatial noise filtering may not be included as part of the temporal loop for temporal filtering (e.g., the spatial noise filter may be applied to an image frame after it is stored as a reference image frame and thus the reference frame is not spatially filtered. 
     Color processing stage  312  may perform various operations associated with adjusting color information in the image data. The operations performed in color processing stage  312  include, but are not limited to, local tone mapping, gain/offset/clip, color correction, three-dimensional color lookup, gamma conversion, and color space conversion. Local tone mapping refers to spatially varying local tone curves in order to provide more control when rendering an image. For instance, a two-dimensional grid of tone curves (which may be programmed by the central control module  320 ) may be bi-linearly interpolated such that smoothly varying tone curves are created across an image. In some embodiments, local tone mapping may also apply spatially varying and intensity varying color correction matrices, which may, for example, be used to make skies bluer while turning down blue in the shadows in an image. Digital gain/offset/clip may be provided for each color channel or component of image data. Color correction may apply a color correction transform matrix to image data. 3D color lookup may utilize a three dimensional array of color component output values (e.g., R, G, B) to perform advanced tone mapping, color space conversions, and other color transforms. Gamma conversion may be performed, for example, by mapping input image data values to output data values in order to perform gamma correction, tone mapping, or histogram matching. Color space conversion may be implemented to convert image data from one color space to another (e.g., RGB to YCbCr). Other processing techniques may also be performed as part of color processing stage  312  to perform other special image effects, including black and white conversion, sepia tone conversion, negative conversion, or solarize conversion. 
     Output rescale module  314  may resample, transform and correct distortion on the fly as the ISP  206  processes image data. Output rescale module  314  may compute a fractional input coordinate for each pixel and uses this fractional coordinate to interpolate an output pixel via a polyphase resampling filter. A fractional input coordinate may be produced from a variety of possible transforms of an output coordinate, such as resizing or cropping an image (e.g., via a simple horizontal and vertical scaling transform), rotating and shearing an image (e.g., via non-separable matrix transforms), perspective warping (e.g., via an additional depth transform) and per-pixel perspective divides applied in piecewise in strips to account for changes in image sensor during image data capture (e.g., due to a rolling shutter), and geometric distortion correction (e.g., via computing a radial distance from the optical center in order to index an interpolated radial gain table, and applying a radial perturbance to a coordinate to account for a radial lens distortion). 
     Output rescale module  314  may apply transforms to image data as it is processed at output rescale module  314 . Output rescale module  314  may include horizontal and vertical scaling components. The vertical portion of the design may implement series of image data line buffers to hold the “support” needed by the vertical filter. As ISP  206  may be a streaming device, it may be that only the lines of image data in a finite-length sliding window of lines are available for the filter to use. Once a line has been discarded to make room for a new incoming line, the line may be unavailable. Output rescale module  314  may statistically monitor computed input Y coordinates over previous lines and use it to compute an optimal set of lines to hold in the vertical support window. For each subsequent line, output rescale module may automatically generate a guess as to the center of the vertical support window. In some embodiments, output rescale module  314  may implement a table of piecewise perspective transforms encoded as digital difference analyzer (DDA) steppers to perform a per-pixel perspective transformation between a input image data and output image data in order to correct artifacts and motion caused by sensor motion during the capture of the image frame. Output rescale may provide image data via output interface  316  to various other components of device  100 , as discussed above with regard to  FIGS. 1 and 2 . 
     In various embodiments, the functionally of components  302  through  350  may be performed in a different order than the order implied by the order of these functional units in the image processing pipeline illustrated in  FIG. 3 , or may be performed by different functional components than those illustrated in  FIG. 3 . Moreover, the various components as described in  FIG. 3  may be embodied in various combinations of hardware, firmware or software. 
     Example Architecture of Color Processing Stage  312   
       FIG. 4  is a block diagram of the color processing stage  312  according to one embodiment. As mentioned above with reference to  FIG. 3 , the color processing stage  312  performs various operations associated with adjusting color information in image data. The operations for adjusting color information in image data include a color space conversion to convert image data from one color space to another. 
     In one embodiment, the color processing stage  312  includes an HDR color space converter  401 . The HDR color space converter  401  converts image data from a non-HDR color space to an HDR color space. In particular, the HDR color space converter  401  includes an HDR circuit  403  that receives image data  411  and converts the image data  411  from one color space to an HDR color space. That is, the HDR circuit  403  converts pixel values of the image data  411  (e.g., the input image pixel values) into output image pixel values  413  that are in an HDR color space. The output image pixel values  413  can be stored in the system memory  230  for further processing and/or display on display  216 . 
     The HDR circuit  403  converts the pixel values of the image data  411  using a color conversion function that is selected from multiple different types of color conversion functions. Each type of color conversion function has different mappings of input image pixel values from the image data  411  to output pixel conversion values for HDR format. 
       FIG. 5  is a detailed block diagram of the HDR circuit  403 , according to one embodiment. The HDR circuit  403  includes, among other components, a first color space converter  501 , a second color space converter  505 , and a third color space converter  515 . The first color space converter  501  receives the image data  411 . The image data  411  may be in a YCbCr color format or other non-HDR formats. The first color space converter  601  converts the image data  411  into a different color space. In one embodiment, the first color space converter  501  converts the image data  411  in the YCbCr color format to the LMS color space. The first color space converter  501  may first convert the image data  411  in YCbCr color format to the RGB color space and then convert the merged fused image data in the RGB color space to the LMS color space. The first color space converter  501  outputs the converted image data  503  in the LMS color space to the second color space converter  505 . The second color space converter  505  converts the converted image data  503  according to a color conversion function. The color conversion function used for HDR color conversion is dependent on the operation mode of the HDR circuit  403 . 
     The second color space converter  505  may include, among other components, a mode register  509  that defines an operation mode of the HDR circuit  403 , a symmetry register  511  that specifies whether the color conversion function used in the operation mode of the HDR circuit  403  includes symmetry, a sample register  513  that defines the number of sample points in different regions of the color conversion function, and a look up table (LUT)  507  that stores a mapping of input pixel conversion values and output pixel conversion values for the color conversion function used in the mode of operation specified in the mode register  509 , as will be described in further detail below. Note that in other embodiments, the second color space converter  505  may include other components than shown in  FIG. 5 . 
     The mode register  509  stores a mode value that defines an operation mode of the HDR circuit  403 . The HDR circuit  403  may operate in one of a plurality of different operation modes where each operation mode uses a corresponding color conversion function to perform HDR color conversion. For example, a mode value of “1” places the HDR circuit  403  in a first operation mode that uses a first type of color conversion function for HDR color conversion, a mode value of “2” places the HDR circuit  403  in a second operation mode that uses a second type of color conversion function for HDR color conversion, a mode value of “3” places the HDR circuit  403  in a third operation mode that uses a third type of color conversion function for HDR color conversion, and a mode value of “4” places the HDR circuit  403  in a fourth operation mode that uses a second type of color conversion function for HDR color conversion. 
     The HDR circuit  403  may operate in one of four different operation modes where each operation mode uses a different type of color conversion function from a plurality of different types color conversion functions that are available to perform HDR color conversion as described below. While the embodiments described herein use four different types color conversion functions, any number of color conversion functions may be available for HDR color conversion. 
       FIG. 6A  is an example of a first type of color conversion function  601  used in a first operation mode of the HDR circuit  403  according to one embodiment. The first type of color conversion function  601  is characterized as having a steep portion of the curve closest to zero. Examples of the first type of color conversion function  601  include a gamma function, log 2 function, and a power function with an exponent less than 1. 
     In one embodiment, the X-axis of the first type of color conversion function  601  represents the input pixel conversion values that correspond to input image pixel values of the image data  503  in the LMS color space. The Y-axis of the first type of color conversion function  601  represents the output pixel conversion values (e.g., color converted values) where each output pixel conversion value corresponds to one input pixel conversion value. The output pixel conversion values of the first type of color conversion function  601  are applied to the input pixel values of an image to convert the input pixel values into color converted versions of the input pixel values for further processing or displaying on display  100 . 
     Generally, the input pixel conversion values of all of the different color conversion functions are grouped into two regions: Region 1 and Region 2. Region 1 (e.g., a first input range) of the color conversion function is applied to convert input image pixel values from zero signal to input image pixel value X1 into their corresponding output pixel conversion value. Region 2 (e.g., a second input range) of the color conversion function is used to convert input image pixel values X1+1 to X2 into their corresponding output pixel conversion value. 
     The input image pixel values in Region 1 of the first type of color conversion function  601  can cause distortion when input image pixel values in Region 1 are converted using linear interpolation due to the steepness of the first type of color conversion function  601  in Region 1. To address the issue, the lookup table (LUT)  507  stores output pixel conversion values for each and every input pixel conversion value in Region 1. Thus, Region 1 typically has denser sampling points (e.g., a greater number of sampling points) in the LUT  507  compared to the number of sampling points for Region 2 in the LUT  507 . In one embodiment, the LUT  507  is embodied as a memory circuit. 
     In one embodiment, the LUT  507  stores a mapping of output pixel conversion values for all input image pixel values in Region 1 of the first type of color conversion function  601 . For each pixel in the converted image data  503  having an input image pixel value in Region 1 of the color conversion function, the second color space converter  505  accesses the LUT  507  to identify the output pixel conversion value that maps to the input image pixel value of the image. The output pixel conversion value that maps to the input image pixel value is a color converted version of the input image pixel value. Note that the LUT  507  may have multiple conversion tables for the different color components in the LMS color space if the L, M, S components have different color conversion functions. That is, the LUT  507  may have a conversion table for the “L” component, the “M” component, and the “S” component of the converted image data  503 , respectively. In another embodiment, the LUT  507  has a single conversion table for the L, M, and S components if the color conversion function for the L, M, and S components are the same. 
     In one embodiment, the LUT  507  also stores output pixel conversion values for input image pixel values in Region 2 of the first type of color conversion function  601 . However, unlike for Region 1 of the first type of color conversion function  601 , the LUT  507  stores output pixel conversion values for a subset of all possible input pixel conversion values in Region 2 of the first type of color conversion function  601 . The portion of the LUT  507  corresponding to Region 2 of the first type of color conversion function  601  may have input pixel conversion values spaced apart by a power of two and their corresponding output pixel conversion values. That is, adjacent ones of the subset of input pixel values in Region 2 have intervals of power of two. In contrast, LUT  507  stores for Region 1 of the color conversion function each input pixel conversion value in Region 1 and its corresponding output pixel conversion value as described above. 
     In one embodiment, the set of output pixel conversion values that are stored in LUT  507  are dependent on the operation mode of the HDR circuit  403 . As mentioned above, each operation mode of the HDR circuit  403  uses a different color conversion function to perform HDR color conversion. Accordingly, each operation mode of the HDR circuit  403  uses a unique set of output pixel conversion values that is associated with the color conversion function that corresponds to the operation mode. The unique set of output pixel conversion values that is loaded into the LUT  507  is based on the operation mode of the HDR circuit  403 . 
     Referring back to  FIG. 5 , the second color space converter  505  further includes a sample register  513  according to one embodiment. The sample register  513  stores values defining the number of sample points (e.g., input pixel conversion values and output pixel conversion values) that are included in each of Region 1 and Region 2 of the color conversion function used in the operation mode of the HDR circuit  403 . In one embodiment, the total number of sample points that are included in Region 1 and Region 2 are the same for all of the different modes of the HDR circuit  403 . For example, the LUT  507  may store a total of 257 sample points across Region 1 and Region 2 for each color conversion function. However, any number of sample points may be stored in other embodiments. 
     Generally, the total number of sample points included in Region 1 is configurable. In one embodiment, the total amount of sample points included in Region 1 is less than the total number of sample points included in Region 2. However, in other embodiments the total number of sample points included in Region 1 is more than the total number of sample points included in Region 2. Region 1 may include any number of sample points that satisfy all possible input pixel conversion values in Region 1 of the color conversion function given that Region 1 is associated with the steepest portion of the color conversion function. In one embodiment, Region 1 may have n points where n is a positive natural number. 
     Region 2 in contrast is divided into multiple sub-regions. Each sub-region in Region 2 may have the same number of sample points or a different number of sample points as the remaining sub-regions. In one embodiment, Region 2 is divided into multiple sub-regions using a non-uniform integer function. 
       FIG. 6B  illustrates the number of sample points in Region 1 and Region 2 of the first color conversion function  601 . As shown in  FIG. 6B , Region 1 may have n points of input pixel conversion values and output pixel conversion values where n is a positive natural number. In contrast, the sub-regions of Region 2 are divided using a power function (e.g., power of 2). The first sub-region of Region 2 is between points 2 n  and 2 n+1 , the second sub-region of Region 2 is between points 2 n+1  and 2 n+2 , the third sub region of Region 2 is between points 2 n+2  and 2 n+3  and so on. As shown in  FIG. 6B , each sub-region in Region 2 has the same number of sample points. In this example, each sub-region has 2 m  sample points where m is four. However, m can any natural number greater than zero. 
     Furthermore, in other embodiments the number of sample points in each sub-region is configurable such that the number of sample points in each sub-region are different from each other. For example, the first sub-region in Region 2 may have two sample points whereas the second sub-region in Region 2 may have four sample points. 
     For each pixel in the converted image data  503  having an input image pixel value in Region 2 of the color conversion function, the second color space converter  505  accesses the LUT  507  to identify whether the LUT  507  includes an output pixel conversion value that corresponds to the input image pixel value. Responsive to the LUT  507  storing an output pixel conversion value that corresponds to the input image pixel value in Region 2, the second color space converter  505  performs the necessary conversion by fetching the output pixel conversion value that corresponds to the input image pixel value from the LUT  607 . 
     However, if the LUT  507  does not store an output pixel conversion value for the input image pixel value from Region 2 of the color conversion function, additional interpolation is required. Thus, the second color space converter  505  performs interpolation to determine the output pixel conversion value, as described below in detail with respect to  FIG. 6C . The interpolation function described with respect to  FIG. 6C  is applicable to the other types of color conversion functions described herein. 
     In the example shown in  FIG. 6C  that uses the first type of color conversion function  601 , the second color space converter  505  received an image  503  with an input image pixel value I that is within Region 2 of the color conversion function. Given that an output pixel conversion value for input image pixel value I is not stored within LUT  507 , the second color space converter  505  performs linear interpolation to determine the corresponding output pixel conversion value for input image pixel value I. 
     To perform linear interpolation, the second color space converter  505  first identifies the sub-region of Region 2 that includes the input image pixel value I. The second color space converter  505  then identifies two input pixel conversion values stored in the LUT  507  that bound the input image pixel value I within the sub-region of Region 2. One of the two input pixel conversion values has a higher value than the other of the two input pixel conversion values. In this example, the second color space converter  505  determines that the input image pixel value I is in the sub-region between points 2 n+1  and 2 n+2  in Region 2. The second color space converter  505  then determines that the input image pixel value I is between input pixel conversion values X 152  and X 154  in the identified sub-region and retrieves their corresponding output pixel conversion values Y 152  and Y 154 . Then, the second color space converter  505  performs linear interpolation using the two input pixel conversion values X 152  and X 154  and their corresponding output pixel conversion values Y 152  and Y 154  to determine the output pixel conversion value for input image pixel value I (e.g., the color converted version of input image pixel value I). Since all intervals in Region 2 are a power of two, the second color space converter  505  can use a simple shift operation for the linear interpolation for any in-between points thereby avoiding using general division which is computationally more expensive. 
     As mentioned above, Region 1 may have n points where n is a positive natural number. As a result, the total number of points in Region 1 of a color conversion function may not be a power of two thereby resulting in the last interval in the color conversion function not ending in a point that is a power of two. This scenario would require using general division to perform linear interpolation for any points that are in-between input pixel conversion values rather than using the simple shift operation for the linear interpolation. Accordingly, in one embodiment a configurable dummy point  603  may be added as the last point in the color conversion function to make all intervals of the color conversion function a power of two. Thus, the second color space converter  505  can use the simple shift operation for the linear interpolation for any in-between points. 
     As mentioned above, the HDR circuit  403  operates in different operation modes where each mode is associated with a different type of color conversion function.  FIG. 7A  illustrates a second type of color conversion function  701  that can be used for HDR color conversion in a second operation mode of the HDR circuit  403 . The second type of color conversion function  701  is characterized as having values that are arranged from sparse to dense. That is, Region 1 of the second type of color conversion function  701  has less values than Region 2 since Region 2 of the second type of color conversion function  701  is the steepest region of the curve. 
     As shown in  FIG. 7A , the second type of color conversion function  701  is a mirror image of the first type of color conversion function  601  shown in  FIG. 6  with respect to an offset point along the X axis such that the points of the second type of color conversion function  701  are arranged in a sparse to dense manner such that the sparse points are included in Region 1 and the dense points are arranged in Region 2. In contrast, the points of the first type of color conversion function  601  are arranged in a dense to sparse arrangement such that the dense points are included in Region 1 and the sparse points are arranged in Region 2. In one embodiment, the second color space converter  505  transforms the second type of color conversion function  701  using the mapping values for the first type of color conversion function  601  so that the dense points of the second type of color conversion function  701  are included in Region 1 and the sparse points of the second type of color conversion function  701  are included in Region 2. 
     To generate the mapping values for the second type of color conversion function  701  using the mapping values for the first type of color conversion function  601 , the second color space converter  505  performs coordinate translation on the mapping values for the first type of color conversion function  601 . For example, the second color space converter replaces the first value in the mapping values for the first type of color conversion function  601  with the last value in the mapping values for the first type of color conversion function  601 , replaces the second value in the mapping values for the first type of color conversion function  601  with the second to last value in the mapping values for the first type of color conversion function  601 , replaces the third value in the mapping values for the first type of color conversion function  601  with the third to last value in the mapping values for the first type of color conversion function, and so on. The generated mapping values for the second type of color conversion function  701  are stored for later programming into the LUT  507  when the HDR circuit  403  is in the second operation mode. The transformed second type of color conversion function  701  shown in  FIG. 7B  now resembles the first type of color conversion function  601  in that Region 1 now has the densest distribution of sample points compared to Region 2 which has the sparsest distribution of sample points. 
     In one embodiment, the second color space converter  505  performs color conversion during the second operation mode of the HDR circuit  403  in the same manner as described above with respect to the first operation mode of the HDR circuit  403 . That is, for each pixel in the converted image data  503  having an input image pixel value in Region 1 of the second type of color conversion function  701 , the second color space converter  505  accesses the LUT  507  to identify the output pixel conversion value that maps to the input image pixel value of the image. For each pixel in the converted image data  503  having an input image pixel value in Region 2 of the second type of color conversion function  701 , the second color space converter  505  accesses the LUT  507  to identify whether the LUT  507  includes an output pixel conversion value that corresponds to the input image pixel value. Responsive to the LUT  507  storing an output pixel conversion value that corresponds to the input image pixel value in Region 2, the second color space converter  505  performs the necessary conversion by fetching the output pixel conversion value that corresponds to the input image pixel value from the LUT  507 . However, if the LUT  507  does not store an output pixel conversion value for the input image pixel value from Region 2 of the second type of color conversion function  701 , the second color space converter  505  performs linear interpolation as described above. 
     Referring back to  FIG. 5 , the symmetry register  511  stores a symmetry value that indicates a type of symmetry present in the color conversion function used in an operation mode of the HDR circuit  403 . In one embodiment, a first symmetry value indicates a color conversion function is symmetric about an origin of offset in the X-direction whereas a second symmetry value indicates that the color conversion function is symmetric about s point in the X and Y-directions. If a color conversion function has a property of symmetry, the LUT  507  only needs to be programmed with half of the mapping for the color conversion function since the remaining mapping values of the color conversion function is a mirror image of the mapping values stored in the LUT  507 . Thus, the remaining half of the mapping values of the color conversion function may be expanded (e.g., derived) from the mapping values stored in the LUT  507 . 
       FIG. 8A  illustrates a third type of color conversion function  805  used in a third operation mode of the HDR circuit  403  for HDR color conversion. The third type of color conversion function  805  is characterized as having output pixel conversion values that are symmetrical about an origin of offset in the X-direction. An example of the third type of color conversion function  805  is a bell-shape curve or inverse S-curve. 
     As shown in  FIG. 8A , the third type of color conversion function  805  is symmetrical across an input offset point  801 . The input offset point  801  is offset  803  from zero in the X-direction. In one embodiment, third type of color conversion function  805  includes a first portion  807  to the right of the input offset point  801  and a second portion  809  to the left of the input offset point  801 . In the third operation mode of the HDR circuit  403 , only the input pixel conversion values and the output pixel conversion values of the first portion  807  are programmed in LUT  507  as will be described below. 
     The first portion  807  of the third type of color conversion function  805  is similar in shape to the second type of color conversion function  701 . That is, the output pixel correction values of the first portion  807  of the third type of color conversion function  805  have the densest number of points in Region 2 instead of in Region 1. Accordingly, the first portion  807  of the third type of color conversion function  805  is transformed by the second color space converter  505  so that the output pixel conversion values of the transformed portion  807  have dense to sparse properties similar to the first type of color conversion function  601 . 
     To transform the output pixel conversion values for the first portion  807  of the third type of color conversion function  805 , the second color space converter  505  stores in the LUT  507  the last value of the output pixel conversion values for the third type of color conversion function  805  as the first value in the mapping values for the third type of color conversion function  805 , the second to last output pixel conversion value in the set of output pixel conversion values for the third type of color conversion function  805  as the second value in the mapping values for the third type of color conversion function  805 , the third to last value in the set of output pixel conversion values for the third type of color conversion function  805  as the third value in the mapping values for the third type of color conversion function  805 , and so on. The transformed third type of color conversion function  805  shown in  FIG. 8B  now resembles the first type of color conversion function  601  in that Region 1 has the densest distribution of sampling points compared to Region 2 which has the sparsest distribution of sampling points. 
     As shown in  FIG. 8B , the first portion  807  of the transformed third type of color conversion function  807  is divided into Region 1 and Region 2. Similar to the first type of color conversion function  601 , Region 1 may have n points where n is a positive natural number. In contrast, the sub-regions of Region 2 are divided using a power function (e.g., power of 2). The first sub-region of Region 2 is between points 2 n  and 2 n+1 , the second sub-region of Region 2 is between points 2 n+1  and 2 n+2 , the third sub region of Region 2 is between points 2 n+2  and 2 n+3  and so on. As shown in  FIG. 8B , each sub-region in Region 2 has the same number of input pixel conversion values. In this example, each sub-region has 2 m  points where m is 2. However, m can any natural number greater than zero. Furthermore, in other embodiments the number of points in each sub-region is configurable such that the number of points in each sub-region are different from each other. For example, the first sub-region in Region 2 may have two points whereas the second sub-region in Region 2 may have four points. 
     In one embodiment, the mapping values for the second portion  809  of the third type of color conversion function  805  are not stored in the LUT  507 . The second color space converter  505  may derive the mapping values for the second portion  809  of the third type of color conversion function  805  during HDR color conversion from the mapping values for the first portion  807  that are stored in LUT  507 . In one embodiment, the HDR circuit  503  derives the mapping values for the second portion  809  by mirroring the mapping values in the LUT  507  for the first portion  807  of the third type of color conversion function as the mapping values for the second portion  807  of the third type of color conversion function  805 . 
     For example, the input pixel correction value and output pixel conversion value of point  801  of portion  807  of the third type of color conversion function  807  is the first value stored in the LUT  507 . Point  801  has an offset input pixel conversion value  803  from zero. In one embodiment, the second color space converter  505  derives the output pixel conversion values for any input pixel conversion values of the image  503  that fall within the second portion  809  of the third type of color conversion function  807  using the mapping values stored in LUT  507  and the offset input pixel conversion value  803 . 
     For example, the second color space converter  505  derives the value of the first input pixel conversion value for portion  807  by mirroring the value of the first input pixel conversion value for portion  807  in the negative direction from point  801 . If the second input pixel conversion value for the first portion  807  is the sum of the offset input pixel conversion value  803  and a value “X”, the first input pixel conversion value for the second portion  809  is derived as the absolute value of the difference of the value “X” and the offset input pixel conversion value  803 . Since the first and second portions  807  and  809  have symmetrical properties, the second output pixel conversion value for the second portion  809  has the same output pixel conversion value as the second output pixel conversion value for the second portion  807 . The second color space converter  505  derives the remaining input pixel conversion values and output pixel conversion values for the second portion  907  in a similar manner. 
     In one embodiment, the second color space converter  505  performs color conversion during the third mode of the HDR circuit  403  in the same manner as described above with respect to the first and second modes of the HDR circuit  403 . That is, for each pixel in the converted image data  503  having an input image pixel value in Region 1 of the third type of color conversion function  805 , the second color space converter  505  accesses the LUT  507  to identify the output pixel conversion value that maps to the input image pixel value of the image. For each pixel in the converted image data  503  having an input image pixel value in Region 2 of the third type of color conversion function  805 , the second color space converter  505  accesses the LUT  507  to identify whether the LUT  507  includes an output pixel conversion value that corresponds to the input image pixel value. Responsive to the LUT  507  storing an output pixel conversion value that corresponds to the input image pixel value in Region 2, the second color space converter  505  performs the necessary conversion by fetching the output pixel conversion value that corresponds to the input image pixel value from the LUT  507 . However, if the LUT  507  does not store an output pixel conversion value for the input image pixel value from Region 2 of the third type of color conversion function  805 , the second color space converter  505  performs linear interpolation as described above. For any input image pixel values of the image  503  that do not map to mapping values in the LUT  507 , the second color space converter  505  derives the points of the other half of the third type of color conversion function  807  from the mapping values stored in the LUT as described above. 
       FIG. 9A  illustrates a fourth type of color conversion function  901  used in a fourth mode of the HDR circuit  403  for HDR color conversion. The fourth type of color conversion function  901  is characterized as having output pixel conversion values that are symmetrical about a point  903  in the X- and Y-directions. An example of the fourth type of color conversion function  901  is a S-curve. 
     As shown in  FIG. 9A , the fourth type of color conversion function  901  is symmetrical across the point  903 . The point  903  has a magnitude of offset  909  from zero in the Y-direction and a magnitude of offset  913  in the X-direction. In one embodiment, fourth type of color conversion function  901  includes a first portion  905  above the point  903  and a second portion  907  under the point  903 . The first portion  905  of the fourth type of color conversion function  901  that is above the point  903  is similar to the first type of color conversion function  601 . That is, the output pixel correction values of the first portion  905  of the fourth type of color conversion function  905  are already arranged from dense to sparse similar to the first type of color conversion function  601 . Thus, the output pixel correction values (e.g., the mapping values) of the portion  905  are stored in the LUT  507  without requiring any transformation. The output pixel correction values of the portion  907  are not stored in LUT  507  and are instead derived from the mapping values stored in the LUT  507  during the fourth mode of the HDR circuit  404 . 
     Referring to  FIG. 9B , the portion  905  of the fourth type of color conversion function  905  is divided into Region 1 and Region 2. Similar to the first type of color conversion function, Region 1 may have n points where n is a positive natural number. In contrast, the sub-regions of Region 2 are divided using a power function (e.g., power of 2). The first sub-region of Region 2 is between points 2 n  and 2 n+1 , the second sub-region of Region 2 is between points 2 n+1  and 2 n+2 , the third sub region of Region 2 is between points 2 n+2  and 2 n+3  and so on. As shown in  FIG. 9B , each sub-region in Region 2 has the same number of input pixel conversion values. In this example, each sub-region has 2 m  points where m is 2. However, m can any natural number greater than zero. Furthermore, in other embodiments the number of points in each sub-region is configurable such that the number of points in each sub-region are different from each other. For example, the first sub-region in Region 2 may have two points whereas the second sub-region in Region 2 may have four points. 
     In one embodiment, the LUT  507  stores a mapping of output pixel conversion values for all input image pixel values in Region 1 of the fourth type of color conversion function  901  for the fourth mode of the HDR circuit  403  as described above with respect to the first type of color conversion function  601 . For each pixel in the converted image data  503  having an input image pixel value in Region 1 of the color conversion function, the second color space converter  505  accesses the LUT  507  to identify the output pixel conversion value that maps to the input image pixel value of the image. The output pixel conversion value that maps to the input image pixel value is a color converted version of the input image pixel value. 
     The LUT  507  also stores mapping values for input image pixel values in Region 2 of the fourth type of color conversion function  901 . However, unlike for Region 1 of the fourth type of color conversion function  905 , the LUT  507  stores output pixel conversion values for a subset of all possible input pixel conversion values in Region 2 of the color conversion function. The portion of the LUT  507  corresponding to Region 2 of the color conversion function may have input pixel conversion values spaced apart by a power of two and their corresponding output pixel conversion values. That is, adjacent ones of the subset of input pixel values in Region 2 have intervals of power of two. In contrast, LUT  507  stores for Region 1 of the color conversion function each input pixel conversion value in Region 1 and its corresponding output pixel conversion value as described above. 
     For each pixel in the converted image data  403  having an input image pixel value in Region 2 of the fourth type of color conversion function  905 , the second color space converter  505  accesses the LUT  507  to identify whether the LUT  507  includes an output pixel conversion value that corresponds to the input image pixel value. Responsive to the LUT  507  storing an output pixel conversion value that corresponds to the input image pixel value in Region 2, the second color space converter  505  performs the necessary conversion by fetching the output pixel conversion value that corresponds to the input image pixel value from the LUT  607 . However, if the LUT  507  does not store an output pixel conversion value for the input image pixel value from Region 2 of the color conversion function, additional interpolation is required. Thus, the second color space converter  505  performs interpolation to determine the output pixel conversion value as previously described above. 
     In one embodiment, LUT  507  does not store mapping values for the second portion  907  of the fourth type of color conversion function  901 . Rather, the second color space converter  505  derives the mapping values for any input pixel conversion values of the image  503  that fall within the second portion  907  of the fourth type of color conversion function  901  from the mapping values stored in the LUT  507  for the first portion  905  of the fourth type of color conversion function  901 . In one embodiment, the second color space converter  505  derives the input and output pixel conversion values for the second portion  907  by mirroring the input and output pixel conversion values in the LUT  507  for the second portion  905  of the fourth type of color conversion function  905  in the negative direction across the offset point  903 . 
     For example, the input pixel correction value and output pixel conversion value of point  903  of portion  905  of the fourth type of color conversion function  901  is the first value stored in the LUT  507 . Point  903  has an offset input pixel conversion value  913  from zero in the X-direction and an offset output pixel conversion value  909  from zero in the Y-direction. In one embodiment, the second color space converter  505  derives the output pixel conversion values for any input pixel conversion values of the image  503  that fall within the portion  907  of the fourth type of color conversion function  901  using the sampling values for portion  905  and the offset input pixel conversion value  913  and the offset output pixel conversion value  909 . 
     In one embodiment, the second color space converter  505  derives the value of the first input pixel conversion value for portion  907  by mirroring the value of the first input pixel conversion value for portion  905  in the negative direction from point  903 . For example, if the first input pixel conversion value for portion  905  is the sum of the offset input pixel conversion value  913  and a value “X”, the first input pixel conversion value for the portion  907  is the absolute value of the difference of the value “X” and the offset input pixel conversion value  913 . The second color space converter  505  derives the remaining input pixel conversion values for portion  907  in a similar manner. 
     The second color space converter  505  similarly derives the value of the first output pixel conversion value for portion  907  by mirroring the value of the first output pixel conversion value for portion  905  in the negative direction from point  903 . If the first output pixel conversion value for portion  905  is the sum of the offset output pixel conversion value  909  and a value “Y”, the first output pixel conversion value for the portion  907  is the difference of the offset output pixel conversion value  909  and the value “Y”. The second color space converter  505  derives the remaining output pixel conversion values for portion  907  in a similar manner. 
     In one embodiment, the second color space converter  505  performs color conversion during the fourth mode of the HDR circuit  403  in the same manner as described above with respect to the first, second, and third modes of the HDR circuit  403 . That is, for each pixel in the converted image data  503  having an input image pixel value in Region 1 of the fourth type of color conversion function  901 , the second color space converter  505  accesses the LUT  507  to identify the output pixel conversion value that maps to the input image pixel value of the image. For each pixel in the converted image data  503  having an input image pixel value in Region 2 of the fourth type of color conversion function  901 , the second color space converter  505  accesses the LUT  507  to identify whether the LUT  507  includes an output pixel conversion value that corresponds to the input image pixel value. Responsive to the LUT  507  storing an output pixel conversion value that corresponds to the input image pixel value in Region 2, the second color space converter  505  performs the necessary conversion by fetching the output pixel conversion value that corresponds to the input image pixel value from the LUT  507 . However, if the LUT  507  does not store an output pixel conversion value for the input image pixel value from Region 2 of the fourth type of color conversion function  901 , the second color space converter  505  performs linear interpolation as described above. For any input image pixel values of the image  503  that do not map to points in the LUT  507 , the second color space converter  505  derives the points of the other half of the fourth type of color conversion function  901  from the points stored in the LUT to perform color conversion as described above. 
     Referring back to  FIG. 5 , when the second color space converter  505  converts the input image pixel values for the converted image data  503  into converted image data  517 , the second color space converter  505  outputs the converted image data  517  to a third color space converter  515 . The third color space converter  515  converts the converted image data  517  into another color space format. In one embodiment, the third color space converter  515  converts the converted image data  517  into the ICTCP color space which complies with the BT.2100 standard for HDR display. After conversion, the third color space converter  515  outputs the converted image data  413  in the ICTCP color space. 
       FIG. 10  is detailed block diagram of the second color space converter  505 , according to one embodiment. In addition to the registers and LUT  507  shown in  FIG. 5 , the second color space converter  505  includes a comparator circuit  1001 , a fetcher circuit  1003 , a fetcher circuit  1005 , an interpolator circuit  1007 , and a multiplexor  10009  in one embodiment. The comparator circuit  1001  receives the converted image data  503  and determines for each input image pixel value in the converted image data  503  whether the input image pixel value is in Region 1 or Region 2 of the color conversion function. As described above the color conversion function being used for HDR color conversion is selected based on the mode value stored in the mode register  509 . The set of values (e.g., the input pixel conversion values and the output pixel conversion values) of the selected mode are loaded into LUT  507 . 
     In one embodiment, the comparator circuit  1001  determines whether each input image pixel value is above or below a pixel value threshold where the pixel value threshold corresponds to the last pixel value in Region 1 of the color conversion function. If the input image pixel value is less than or equal to the pixel value threshold, the input image pixel value is within Region 1 of the color conversion function and the comparator circuit  1001  provides the input image pixel value to fetcher circuit  1003 . 
     Fetcher circuit  1003  bypasses the interpolator  1007  and fetches from the LUT  507  the output pixel conversion value corresponding to the input image pixel value that is in Region 1 of the color conversion function. The fetcher circuit  1003  provides the output pixel conversion value fetched from the LUT  507  or derived from the output pixel conversion value fetched from LUT  507  to multiplexor  1009  which outputs the converted image data  413  using the fetched output pixel conversion value according to a selection signal SEL3 that is set based on whether the comparator circuit  1001  determines that the input image pixel value is in Region 1 or Region 2 of the color conversion function. 
     If the input image pixel value is greater than the pixel value threshold, the input image pixel value is within Region 2 of the color conversion function and the comparator circuit  1001  provides the input image pixel value to fetcher circuit  1005 . The fetcher circuit  1005  determines whether the input image pixel value is indexed (e.g., mapped) to a corresponding output pixel conversion value within Region 2 of the color conversion function. If the input image pixel value is indexed to a corresponding output pixel conversion value in the LUT  507  or can be derived from the output pixel conversion value in LUT  507 , the fetcher circuit  805  fetches or derives the output pixel conversion value and provides the fetched output pixel conversion value to the multiplexor  1009  through interpolator circuit  1007  without the interpolator  1007  performing interpolation. 
     In one embodiment, during the third and fourth modes of the HDR circuit  403 , the determination of whether the input image pixel value is indexed to a corresponding output pixel conversion value within Region 1 or Region 2 of the color conversion function includes the fetcher circuit  1005  deriving the input pixel conversion values and output pixel conversion values for symmetrical portions of the color conversion functions as not all of the input pixel conversion values and output pixel conversion values are stored in LUT  507  as described above. The fetcher circuit  1005  determines whether the input image pixel value is indexed to a corresponding output pixel conversion value that is derived by the fetcher circuit  1005  based on the values stored in LUT  507 . 
     However, if the input image pixel value within Region 2 of the color conversion function does not index to a corresponding output pixel conversion value in the LUT  507 , the fetcher circuit  1005  fetches from the LUT  507  a pair of input pixel conversion values (derived or stored in LUT  507 ) that bound the input image value and their corresponding output pixel conversion values. In one embodiment, the fetcher circuit  1005  first determines the sub-region of Region 2 of the color conversion function that includes the input image pixel value. Given that Region 2 is divided into sub-regions based on a power of 2 function, the fetcher circuit  805  can identify the sub-region that includes the input image pixel value based on the leading edge of digital representation of the input image pixel value. 
     Consider the example where the input image pixel value is 14. The digital representation of 14 is “00001110” assuming an 8-bit format. The leading edge (e.g., most significant bit with a value of 1) is in the 3 rd  position indicating that the input image pixel value of 14 is in the third sub-region of Region 2. In one embodiment, the values in the digital representation of the input image pixel value after the leading edge indicate the points within the identified sub-region that are used to interpolate the output image pixel conversion value for the input image pixel value. For example, the remaining values of “110” indicate the first and second points within the third-sub region are used for interpolation. 
     The fetcher circuit  1005  outputs the fetched output pixel conversion values and input pixel conversion values from LUT  507  to interpolator  1007 . The interpolator circuit  1007  performs linear interpolation using the fetched output pixel conversion values and the fetched input pixel conversion values to calculate the output image pixel value for the input image pixel value. The interpolator circuit  1007  provides the calculated output image pixel value to multiplexor  1009  which outputs the converted image data  413  using the fetched output image pixel value according to the selection signal SEL3. 
     Example Process for Performing Color Conversion 
       FIG. 11  is a flowchart illustrating a method of pixel conversion, according to one embodiment. The method may include additional or fewer steps, and steps may be performed in different orders. The method may be performed by HDR circuit  403  of  FIG. 4 . The HDR circuit  403  stores  1101  a plurality of mappings between color converted values and input pixel values. Each mapping is associated with a different color conversion function that may be used for HDR color conversion. The HDR circuit  403  operates in different operation modes where each operation mode uses a different color conversion function for HDR color conversion. The different color conversion functions may include a Gamma function, a log 2 function, a power function with an exponent less than 1, a bell-shaped function, an inverse S-curve function, or a S-curve function. 
     The HDR circuit  403  receives  1103  an operation mode instruction that specifies the mode of operation of the HDR circuit  403 . The instruction includes a mode value that is stored in the mode register  509 . As mentioned above, the mode value specifies the operation mode of the HDR circuit  403  where the operation mode corresponds to a specific color conversion function from among the multiple color conversion functions. 
     The HDR circuit  403  selects  1105  a mapping from the plurality of mappings based on the operation mode of the HDR circuit  403 . The selected mapping is loaded into the LUT  507 . The HDR circuit  403  produces  1107  a color converted value as a color converted version of a first input pixel value of an image responsive to the first input pixel value being within a first input range of the color conversion function. The HDR circuit  403  produces  1109  a color converted version of a second input pixel value of the image by interpolating a subset of the color converted values received from the LUT  507  responsive to the second input pixel value within a second input range of the color conversion function. In one embodiment, the second input range distinct from the first input range. 
     While the embodiments herein are described with respect to HDR processing, the principles used for HDR color conversion are applicable to other types of processing that convert data from one format to another. The principles can be applied to other types of image processing or other technology such as sound processing. 
     While particular embodiments and applications have been illustrated and described, it is to be understood that the invention is not limited to the precise construction and components disclosed herein and that various modifications, changes and variations which will be apparent to those skilled in the art may be made in the arrangement, operation and details of the method and apparatus disclosed herein without departing from the spirit and scope of the present disclosure.

Metadata:
Filing Date: 20210216
Publication Date: 20220215
Grant Date: 20220215
Priority Date: 20210216
Inventors: WU, CHIHSIN
POPE, DAVID R.
Assignee: APPLE INC
CPC Classifications: [{"code": "H04N1/6027", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04N1/407", "inventive": false, "first": false, "tree": "[]"}, {"code": "H04N1/6058", "inventive": true, "first": false, "tree": "[]"}, {"code": "H04N1/6025", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04N1/6025", "inventive": true, "first": true, "tree": "[]"}, {"code": "H04N1/6058", "inventive": true, "first": false, "tree": "[]"}]
Family ID: 80249385