Patent Publication Number: US-2023154063-A1

Title: Non-linear filtering for color space conversions

Description:
TECHNICAL FIELD 
     The present disclosure relates generally to processing systems and, more particularly, to one or more techniques for graphics processing. 
     INTRODUCTION 
     Computing devices often perform graphics and/or display processing (e.g., utilizing a graphics processing unit (GPU), a central processing unit (CPU), a display processor, etc.) to render and display visual content. Such computing devices may include, for example, computer workstations, mobile phones such as smartphones, embedded systems, personal computers, tablet computers, and video game consoles. GPUs are configured to execute a graphics processing pipeline that includes one or more processing stages, which operate together to execute graphics processing commands and output a frame. A central processing unit (CPU) may control the operation of the GPU by issuing one or more graphics processing commands to the GPU. Modern day CPUs are typically capable of executing multiple applications concurrently, each of which may need to utilize the GPU during execution. A display processor is configured to convert digital information received from a CPU to analog values and may issue commands to a display panel for displaying the visual content. A device that provides content for visual presentation on a display may utilize a GPU and/or a display processor. 
     A GPU of a device may be configured to perform the processes in a graphics processing pipeline. Further, a display processor or display processing unit (DPU) may be configured to perform the processes of display processing. However, with the advent of wireless communication and smaller, handheld devices, there has developed an increased need for improved graphics or display processing. 
     BRIEF SUMMARY 
     The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later. 
     In an aspect of the disclosure, a method, a computer-readable medium, and an apparatus are provided. The apparatus may be a graphics processing unit (GPU) or any apparatus that may perform graphics processing. The apparatus may transmit a request for a plurality of pixels associated with a first color space, where a plurality of pixels is received based on the transmitted request. The apparatus may also receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel. Additionally, the apparatus may read the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel. The apparatus may also decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. The apparatus may also filter each of the plurality of first color channels after the at least one first color channel is decompressed. Moreover, the apparatus may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels. The apparatus may also transmit the plurality of pixels associated with the second color space after the color space conversion. 
     The details of one or more examples of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the disclosure will be apparent from the description and drawings, and from the claims. 
    
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         FIG.  1    is a block diagram that illustrates an example content generation system. 
         FIG.  2    is an example graphics processing unit (GPU). 
         FIG.  3    is a diagram of components for graphics processing and display/image processing. 
         FIG.  4    includes diagrams illustrating an example linear sampling process and an example gamma space filtering process. 
         FIG.  5 A  is a diagram illustrating an example non-linear YUV encoding process. 
         FIG.  5 B  is a diagram illustrating an example non-linear YUV encoding process. 
         FIG.  6 A  is a diagram illustrating an example non-linear YUV decoding process. 
         FIG.  6 B  is a diagram illustrating an example non-linear YUV decoding process. 
         FIG.  7 A  is a diagram illustrating an example non-linear YUV decoding process with filtering. 
         FIG.  7 B  is a diagram illustrating an example non-linear YUV decoding process with filtering. 
         FIG.  8    is a diagram illustrating an example non-linear YUV encoding process. 
         FIG.  9    is a diagram illustrating an example non-linear YUV decoding process. 
         FIG.  10    is a diagram illustrating an example non-linear YUV decoding process with filtering. 
         FIG.  11    is a communication flow diagram illustrating example communications between GPU components. 
         FIG.  12    is a flowchart of an example method of graphics processing. 
         FIG.  13    is a flowchart of an example method of graphics processing. 
     
    
    
     DETAILED DESCRIPTION 
     Some aspects of graphics processing or image processing may utilize a color space (i.e., a specific organization of colors). There a number of different types of color spaces or color models (i.e., an abstract mathematical model describing the way colors may be represented as tuples of numbers). For example, there are red (R) green (G) blue (B) (RGB) color spaces/models or luminance (Y) chrominance (UV) (YUV) color spaces/models. Additionally, color spaces may be converted from one color space to another color space in a process referred to as color space conversion (i.e., the translation of the representation of a color from one basis to another). A color space conversion may occur in the context of converting an image that is represented in one color space to a representation in another color space. Some aspects of color space conversion may have difficulty filtering in a non-linear space. For example, after an RGB image is generated, in order to preserve bit-rate, the RGB image may be non-linearly (gamma) compressed. The non-linear RGB may be converted to YUV for video encoding and transfer. On the receiving end, the image may be used as part of an image processing pipeline. This process may need filtering, but the YUV image may internally contain non-linear data. The correct sequence may need the YUV image to be converted to non-linear RGB, and then converted to linear RGB before filtering. For arbitrary pixel access, this sequence may be computationally intense and may not be directly supported by hardware. In addition to difficulty filtering in a non-linear space, some aspects of color space conversion may have difficulty converting to a linear space. Also, the conversion of non-linear YUV samples to linear space may be complex and difficult to implement efficiently in hardware or software. Aspects of the present disclosure may include non-linear YUV conversion processes that filter in a non-linear space. Also, aspects of the present disclosure may convert to a linear space during a non-linear YUV conversion process. For instance, aspects of the present disclosure may convert non-linear YUV samples to a linear space during a non-linear YUV conversion process. Additionally, in some instances, aspects of the present disclosure may include non-linear YUV conversion processes that utilize up-sampling and color space conversion operations with non-linear values. 
     Various aspects of systems, apparatuses, computer program products, and methods are described more fully hereinafter with reference to the accompanying drawings. This disclosure may, however, be embodied in many different forms and should not be construed as limited to any specific structure or function presented throughout this disclosure. Rather, these aspects are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art. Based on the teachings herein one skilled in the art should appreciate that the scope of this disclosure is intended to cover any aspect of the systems, apparatuses, computer program products, and methods disclosed herein, whether implemented independently of, or combined with, other aspects of the disclosure. For example, an apparatus may be implemented or a method may be practiced using any number of the aspects set forth herein. In addition, the scope of the disclosure is intended to cover such an apparatus or method which is practiced using other structure, functionality, or structure and functionality in addition to or other than the various aspects of the disclosure set forth herein. Any aspect disclosed herein may be embodied by one or more elements of a claim. 
     Although various aspects are described herein, many variations and permutations of these aspects fall within the scope of this disclosure. Although some potential benefits and advantages of aspects of this disclosure are mentioned, the scope of this disclosure is not intended to be limited to particular benefits, uses, or objectives. Rather, aspects of this disclosure are intended to be broadly applicable to different wireless technologies, system configurations, networks, and transmission protocols, some of which are illustrated by way of example in the figures and in the following description. The detailed description and drawings are merely illustrative of this disclosure rather than limiting, the scope of this disclosure being defined by the appended claims and equivalents thereof. 
     Several aspects are presented with reference to various apparatus and methods. These apparatus and methods are described in the following detailed description and illustrated in the accompanying drawings by various blocks, components, circuits, processes, algorithms, and the like (collectively referred to as “elements”). These elements may be implemented using electronic hardware, computer software, or any combination thereof. Whether such elements are implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. 
     By way of example, an element, or any portion of an element, or any combination of elements may be implemented as a “processing system” that includes one or more processors (which may also be referred to as processing units). Examples of processors include microprocessors, microcontrollers, graphics processing units (GPUs), general purpose GPUs (GPGPUs), central processing units (CPUs), application processors, digital signal processors (DSPs), reduced instruction set computing (RISC) processors, systems-on-chip (SOC), baseband processors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), programmable logic devices (PLDs), state machines, gated logic, discrete hardware circuits, and other suitable hardware configured to perform the various functionality described throughout this disclosure. One or more processors in the processing system may execute software. Software may be construed broadly to mean instructions, instruction sets, code, code segments, program code, programs, subprograms, software components, applications, software applications, software packages, routines, subroutines, objects, executables, threads of execution, procedures, functions, etc., whether referred to as software, firmware, middleware, microcode, hardware description language, or otherwise. The term application may refer to software. As described herein, one or more techniques may refer to an application, i.e., software, being configured to perform one or more functions. In such examples, the application may be stored on a memory, e.g., on-chip memory of a processor, system memory, or any other memory. Hardware described herein, such as a processor may be configured to execute the application. For example, the application may be described as including code that, when executed by the hardware, causes the hardware to perform one or more techniques described herein. As an example, the hardware may access the code from a memory and execute the code accessed from the memory to perform one or more techniques described herein. In some examples, components are identified in this disclosure. In such examples, the components may be hardware, software, or a combination thereof. The components may be separate components or sub-components of a single component. 
     Accordingly, in one or more examples described herein, the functions described may be implemented in hardware, software, or any combination thereof. If implemented in software, the functions may be stored on or encoded as one or more instructions or code on a computer-readable medium. Computer-readable media includes computer storage media. Storage media may be any available media that may be accessed by a computer. By way of example, and not limitation, such computer-readable media may comprise a random access memory (RAM), a read-only memory (ROM), an electrically erasable programmable ROM (EEPROM), optical disk storage, magnetic disk storage, other magnetic storage devices, combinations of the aforementioned types of computer-readable media, or any other medium that may be used to store computer executable code in the form of instructions or data structures that may be accessed by a computer. 
     In general, this disclosure describes techniques for having a graphics processing pipeline in a single device or multiple devices, improving the rendering of graphical content, and/or reducing the load of a processing unit, i.e., any processing unit configured to perform one or more techniques described herein, such as a GPU. For example, this disclosure describes techniques for graphics processing in any device that utilizes graphics processing. Other example benefits are described throughout this disclosure. 
     As used herein, instances of the term “content” may refer to “graphical content,” “image,” and vice versa. This is true regardless of whether the terms are being used as an adjective, noun, or other parts of speech. In some examples, as used herein, the term “graphical content” may refer to a content produced by one or more processes of a graphics processing pipeline. In some examples, as used herein, the term “graphical content” may refer to a content produced by a processing unit configured to perform graphics processing. In some examples, as used herein, the term “graphical content” may refer to a content produced by a graphics processing unit. 
     In some examples, as used herein, the term “display content” may refer to content generated by a processing unit configured to perform displaying processing. In some examples, as used herein, the term “display content” may refer to content generated by a display processing unit. Graphical content may be processed to become display content. For example, a graphics processing unit may output graphical content, such as a frame, to a buffer (which may be referred to as a framebuffer). A display processing unit may read the graphical content, such as one or more frames from the buffer, and perform one or more display processing techniques thereon to generate display content. For example, a display processing unit may be configured to perform composition on one or more rendered layers to generate a frame. As another example, a display processing unit may be configured to compose, blend, or otherwise combine two or more layers together into a single frame. A display processing unit may be configured to perform scaling, e.g., upscaling or downscaling, on a frame. In some examples, a frame may refer to a layer. In other examples, a frame may refer to two or more layers that have already been blended together to form the frame, i.e., the frame includes two or more layers, and the frame that includes two or more layers may subsequently be blended. 
       FIG.  1    is a block diagram that illustrates an example content generation system  100  configured to implement one or more techniques of this disclosure. The content generation system  100  includes a device  104 . The device  104  may include one or more components or circuits for performing various functions described herein. In some examples, one or more components of the device  104  may be components of an SOC. The device  104  may include one or more components configured to perform one or more techniques of this disclosure. In the example shown, the device  104  may include a processing unit  120 , a content encoder/decoder  122 , and a system memory  124 . In some aspects, the device  104  may include a number of optional components, e.g., a communication interface  126 , a transceiver  132 , a receiver  128 , a transmitter  130 , a display processor  127 , and one or more displays  131 . Reference to the display  131  may refer to the one or more displays  131 . For example, the display  131  may include a single display or multiple displays. The display  131  may include a first display and a second display. The first display may be a left-eye display and the second display may be a right-eye display. In some examples, the first and second display may receive different frames for presentment thereon. In other examples, the first and second display may receive the same frames for presentment thereon. In further examples, the results of the graphics processing may not be displayed on the device, e.g., the first and second display may not receive any frames for presentment thereon. Instead, the frames or graphics processing results may be transferred to another device. In some aspects, this may be referred to as split-rendering. 
     The processing unit  120  may include an internal memory  121 . The processing unit  120  may be configured to perform graphics processing, such as in a graphics processing pipeline  107 . The content encoder/decoder  122  may include an internal memory  123 . In some examples, the device  104  may include a display processor, such as the display processor  127 , to perform one or more display processing techniques on one or more frames generated by the processing unit  120  before presentment by the one or more displays  131 . The display processor  127  may be configured to perform display processing. For example, the display processor  127  may be configured to perform one or more display processing techniques on one or more frames generated by the processing unit  120 . The one or more displays  131  may be configured to display or otherwise present frames processed by the display processor  127 . In some examples, the one or more displays  131  may include one or more of: a liquid crystal display (LCD), a plasma display, an organic light emitting diode (OLED) display, a projection display device, an augmented reality display device, a virtual reality display device, a head-mounted display, or any other type of display device. 
     Memory external to the processing unit  120  and the content encoder/decoder  122 , such as system memory  124 , may be accessible to the processing unit  120  and the content encoder/decoder  122 . For example, the processing unit  120  and the content encoder/decoder  122  may be configured to read from and/or write to external memory, such as the system memory  124 . The processing unit  120  and the content encoder/decoder  122  may be communicatively coupled to the system memory  124  over a bus. In some examples, the processing unit  120  and the content encoder/decoder  122  may be communicatively coupled to each other over the bus or a different connection. 
     The content encoder/decoder  122  may be configured to receive graphical content from any source, such as the system memory  124  and/or the communication interface  126 . The system memory  124  may be configured to store received encoded or decoded graphical content. The content encoder/decoder  122  may be configured to receive encoded or decoded graphical content, e.g., from the system memory  124  and/or the communication interface  126 , in the form of encoded pixel data. The content encoder/decoder  122  may be configured to encode or decode any graphical content. 
     The internal memory  121  or the system memory  124  may include one or more volatile or non-volatile memories or storage devices. In some examples, internal memory  121  or the system memory  124  may include RAM, SRAM, DRAM, erasable programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), flash memory, a magnetic data media or an optical storage media, or any other type of memory. 
     The internal memory  121  or the system memory  124  may be a non-transitory storage medium according to some examples. The term “non-transitory” may indicate that the storage medium is not embodied in a carrier wave or a propagated signal. However, the term “non-transitory” should not be interpreted to mean that internal memory  121  or the system memory  124  is non-movable or that its contents are static. As one example, the system memory  124  may be removed from the device  104  and moved to another device. As another example, the system memory  124  may not be removable from the device  104 . 
     The processing unit  120  may be a central processing unit (CPU), a graphics processing unit (GPU), a general purpose GPU (GPGPU), or any other processing unit that may be configured to perform graphics processing. In some examples, the processing unit  120  may be integrated into a motherboard of the device  104 . In some examples, the processing unit  120  may be present on a graphics card that is installed in a port in a motherboard of the device  104 , or may be otherwise incorporated within a peripheral device configured to interoperate with the device  104 . The processing unit  120  may include one or more processors, such as one or more microprocessors, GPUs, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), arithmetic logic units (ALUs), digital signal processors (DSPs), discrete logic, software, hardware, firmware, other equivalent integrated or discrete logic circuitry, or any combinations thereof. If the techniques are implemented partially in software, the processing unit  120  may store instructions for the software in a suitable, non-transitory computer-readable storage medium, e.g., internal memory  121 , and may execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Any of the foregoing, including hardware, software, a combination of hardware and software, etc., may be considered to be one or more processors. 
     The content encoder/decoder  122  may be any processing unit configured to perform content decoding. In some examples, the content encoder/decoder  122  may be integrated into a motherboard of the device  104 . The content encoder/decoder  122  may include one or more processors, such as one or more microprocessors, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), arithmetic logic units (ALUs), digital signal processors (DSPs), video processors, discrete logic, software, hardware, firmware, other equivalent integrated or discrete logic circuitry, or any combinations thereof. If the techniques are implemented partially in software, the content encoder/decoder  122  may store instructions for the software in a suitable, non-transitory computer-readable storage medium, e.g., internal memory  123 , and may execute the instructions in hardware using one or more processors to perform the techniques of this disclosure. Any of the foregoing, including hardware, software, a combination of hardware and software, etc., may be considered to be one or more processors. 
     In some aspects, the content generation system  100  may include an optional communication interface  126 . The communication interface  126  may include a receiver  128  and a transmitter  130 . The receiver  128  may be configured to perform any receiving function described herein with respect to the device  104 . Additionally, the receiver  128  may be configured to receive information, e.g., eye or head position information, rendering commands, or location information, from another device. The transmitter  130  may be configured to perform any transmitting function described herein with respect to the device  104 . For example, the transmitter  130  may be configured to transmit information to another device, which may include a request for content. The receiver  128  and the transmitter  130  may be combined into a transceiver  132 . In such examples, the transceiver  132  may be configured to perform any receiving function and/or transmitting function described herein with respect to the device  104 . 
     Referring again to  FIG.  1   , in certain aspects, the processing unit  120  may include a determination component  198  configured to transmit a request for a plurality of pixels associated with a first color space, where a plurality of pixels is received based on the transmitted request. The determination component  198  may also be configured to receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel. The determination component  198  may also be configured to read the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel. The determination component  198  may also be configured to decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. The determination component  198  may also be configured to filter each of the plurality of first color channels after the at least one first color channel is decompressed. The determination component  198  may also be configured to perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels. The determination component  198  may also be configured to transmit the plurality of pixels associated with the second color space after the color space conversion. Although the following description may be focused on display processing, the concepts described herein may be applicable to other similar processing techniques. 
     As described herein, a device, such as the device  104 , may refer to any device, apparatus, or system configured to perform one or more techniques described herein. For example, a device may be a server, a base station, user equipment, a client device, a station, an access point, a computer, e.g., a personal computer, a desktop computer, a laptop computer, a tablet computer, a computer workstation, or a mainframe computer, an end product, an apparatus, a phone, a smart phone, a server, a video game platform or console, a handheld device, e.g., a portable video game device or a personal digital assistant (PDA), a wearable computing device, e.g., a smart watch, an augmented reality device, or a virtual reality device, a non-wearable device, a display or display device, a television, a television set-top box, an intermediate network device, a digital media player, a video streaming device, a content streaming device, an in-car computer, any mobile device, any device configured to generate graphical content, or any device configured to perform one or more techniques described herein. Processes herein may be described as performed by a particular component (e.g., a GPU), but, in further embodiments, may be performed using other components (e.g., a CPU), consistent with disclosed embodiments. 
     GPUs may process multiple types of data or data packets in a GPU pipeline. For instance, in some aspects, a GPU may process two types of data or data packets, e.g., context register packets and draw call data. A context register packet may be a set of global state information, e.g., information regarding a global register, shading program, or constant data, which may regulate how a graphics context will be processed. For example, context register packets may include information regarding a color format. In some aspects of context register packets, there may be a bit that indicates which workload belongs to a context register. Also, there may be multiple functions or programming running at the same time and/or in parallel. For example, functions or programming may describe a certain operation, e.g., the color mode or color format. Accordingly, a context register may define multiple states of a GPU. 
     Context states may be utilized to determine how an individual processing unit functions, e.g., a vertex fetcher (VFD), a vertex shader (VS), a shader processor, or a geometry processor, and/or in what mode the processing unit functions. In order to do so, GPUs may use context registers and programming data. In some aspects, a GPU may generate a workload, e.g., a vertex or pixel workload, in the pipeline based on the context register definition of a mode or state. Certain processing units, e.g., a VFD, may use these states to determine certain functions, e.g., how a vertex is assembled. As these modes or states may change, GPUs may need to change the corresponding context. Additionally, the workload that corresponds to the mode or state may follow the changing mode or state. 
       FIG.  2    illustrates an example GPU  200  in accordance with one or more techniques of this disclosure. As shown in  FIG.  2   , GPU  200  includes command processor (CP)  210 , draw call packets  212 , VFD  220 , VS  222 , vertex cache (VPC)  224 , triangle setup engine (TSE)  226 , rasterizer (RAS)  228 , Z process engine (ZPE)  230 , pixel interpolator (PI)  232 , fragment shader (FS)  234 , render backend (RB)  236 , level 2 (L2) cache (UCHE)  238 , and system memory  240 . Although  FIG.  2    displays that GPU  200  includes processing units  220 - 238 , GPU  200  may include a number of additional processing units. Additionally, processing units  220 - 238  are merely an example and any combination or order of processing units may be used by GPUs according to the present disclosure. GPU  200  also includes command buffer  250 , context register packets  260 , and context states  261 . 
     As shown in  FIG.  2   , a GPU may utilize a CP, e.g., CP  210 , or hardware accelerator to parse a command buffer into context register packets, e.g., context register packets  260 , and/or draw call data packets, e.g., draw call packets  212 . The CP  210  may then send the context register packets  260  or draw call data packets  212  through separate paths to the processing units or blocks in the GPU. Further, the command buffer  250  may alternate different states of context registers and draw calls. For example, a command buffer may be structured in the following manner: context register of context N, draw call(s) of context N, context register of context N+1, and draw call(s) of context N+1. 
     GPUs may render images in a variety of different ways. In some instances, GPUs may render an image using rendering and/or tiled rendering. In tiled rendering GPUs, an image may be divided or separated into different sections or tiles. After the division of the image, each section or tile may be rendered separately. Tiled rendering GPUs may divide computer graphics images into a grid format, such that each portion of the grid, i.e., a tile, is separately rendered. In some aspects, during a binning pass, an image may be divided into different bins or tiles. In some aspects, during the binning pass, a visibility stream may be constructed where visible primitives or draw calls may be identified. In contrast to tiled rendering, direct rendering does not divide the frame into smaller bins or tiles. Rather, in direct rendering, the entire frame is rendered at a single time. Additionally, some types of GPUs may allow for both tiled rendering and direct rendering. 
     In aspects of graphics processing or display/image processing, a number of different objects or colors may be adjusted or enhanced in an image or frame. By doing so, the objects or colors in an image may be improved, which may improve the overall appearance of the image. In order to adjust or enhance the objects or colors in an image, the objects or colors may need to be identified prior to the adjustment or enhancement. In some instances, this process may be performed in an image processing pipeline or a display processing pipeline. Moreover, this process may be referred to as an object or color identification process. 
       FIG.  3    illustrates a diagram  300  of components for graphics or display/image processing. For instance,  FIG.  3    illustrates an example structure for an object or color classification process. As shown in  FIG.  3   , diagram  300  may include input  310 , image downscaler  320 , frame selection step  322 , pixel classifier  330 , and multiplexer (MUX)  340 . Diagram  300  can also include a content source, which can include a GPU  350  and/or a video decoder  352 . Additionally, diagram  300  may include artificial intelligence (AI) processor  360 , CPU software  370 , memory  380 , image post-processing unit  390 , and output  392 . The input  310  of diagram  300  may include an image or image sequence. Also, the output  392  of diagram  300  may include the image or image sequence after processing. 
     As shown in  FIG.  3   , input  310  may communicate with image downscaler  320 , pixel classifier  330 , and image post-processing unit  390 . Also, image downscaler  320  may communicate with frame selection step  322 , e.g., to select a frame or image. Further, frame selection step  322  may communicate, e.g., a reduced resolution image, with AI processor  360  and/or CPU software  370 , e.g., via memory  380 . AI processor  360  may also communicate with CPU software  370  via memory  380 . GPU  350  and video decoder  352  may communicate with MUX  340 , e.g., via memory  380 . MUX  340  may also communicate with input  310 . Also, CPU software  370  may communicate with pixel classifier  330 , e.g., a configuration update, and/or image post-processing unit  390 . Pixel classifier  330  may also communicate with image post-processing unit  390 . After this, image post-processing unit  390  may communicate with the output  392 , e.g., an image or image sequence. 
     As further depicted in  FIG.  3   , the image post-processing unit  390  may be pre-frame composition or post-frame composition. In some aspects, diagram  300  may include a low-power real-time pixel processing pipeline, which may include input  310 , image downscaler  320 , pixel classifier  330 , and/or image post-processing unit  390 . Also, diagram  300  may include non-real-time processing, which may be performed on selected images or frames. This non-real-time processing may include frame selection step  322 , MUX  340 , GPU  350 , video decoder  352 , AI processor  360 , CPU software  370 , and memory  380 . In some aspects, AI processor  360  may be referred to as a neural network processor. Also, the CPU software  370  may be utilized for a statistical analysis. 
     Some aspects of graphics processing or image processing may utilize a color space (i.e., a specific organization of colors). A color space may support a reproducible representation of color, such as via an analog or a digital representation. Also, a color space may help to provide the color capabilities of a particular device or digital file. For instance, when trying to reproduce color on a device, color spaces may show details of shadows/highlights and/or color saturation. There a number of different types of color spaces or color models (i.e., an abstract mathematical model describing the way colors may be represented as tuples of numbers). For example, there are red (R) green (G) blue (B) (RGB) color spaces/models or luminance (Y) chrominance (UV) (YUV) color spaces/models. 
     Additionally, color spaces may be converted from one color space to another color space in a process referred to as color space conversion (i.e., the translation of the representation of a color from one basis to another). A color space conversion may occur in the context of converting an image that is represented in one color space to a representation in another color space. For instance, one objective of a color space conversion may be to make a converted image look as similar as possible to an original image. One example of a color space conversion is converting an RGB color space to a YUV color space, or vice versa. 
     In some aspects, the use of YUV color space may be convenient for video streams of natural images. For example, it may be straightforward to encode and decode a full image (e.g., a one-to-one pixel ratio) between an RGB color space and a YUV color space. However, in an image processing pipeline that utilizes filtering from the YUV image, the encoding/decoding process may be difficult if the source image is non-linear (i.e., gamma) compressed with certain types of color space (e.g., a standard RGB (sRGB) color space). 
     Moreover, filtering may be utilized if a certain image (e.g., a YUV image) is part of an image processing or rendering pipeline that may apply scaling, rotations, or other arbitrary image access. If the source is linear RGB then filtering may be performed directly from the resulting YUV. If the source is non-linear (i.e., gamma) compressed sRGB, it may not be possible to correctly filter from the resulting YUV as the Y/U/V components are accumulations of non-linear R/G/B components. Instead, each sample may be converted from YUV to sRGB, then from sRGB to linear RGB before being filtered. Applying these conversions for all samples for an advanced (i.e., bi-cubic) filtering kernel may be costly. This may be even more complex when dealing with subsampled chroma. 
     As indicated above, YUV is a color encoding system based on human perception. For instance, Y=luminance (i.e., linear) or Y′=luma (i.e., non-linear) is the brightness value, to which the human eye is most sensitive. Another color encoding system based on human perception is YCbCr, which is similar to YUV except that the chrominance component is CbCr instead of UV. Chrominance (e.g., consisting of U/Cb (blue projection) and V/Cr (red projection)) is the color values to which the human eye is less sensitive, hence these values can be down-sampled. In some instances, YUV may be associated with analog television systems, while YCbCr may be the digital video equivalent. 
     As further indicated above, RGB and YUV may be utilized in different processes. For example, RGB may be utilized as a common color encoding system for computer images, while YUV may be typically utilized for a video transfer. The transfer between RGB and YUV may be a relatively straight forward process, such as the conversion of one channel in RGB (e.g., R/G/B) to a corresponding channel in YUV (e.g., Y/U/V). For instance, various industry standards may result in a weighted sum of the three components of RGB or YUV (e.g., R/G/B or Y/U/V) plus an offset and/or a scale. 
     Gamma compression is a non-linear transfer function that allows a higher dynamic range color to be stored at limited bitrate based on human perception sensitivity. For example, gamma compression may utilize more bits for the darker regions and fewer bits for the bright regions. The gamma curve may be frequently represented as a straight exponent (e.g., an exponent of 2.2), but various standards may have slight adjustments and/or clamping specifications. Additionally, gamma correction may be frequently implemented using a look-up table (LUT). Although the gamma curve may have been historically associated with the light response of television sets, in modern computer graphics the gamma curve may be used for its bitrate compression capabilities. 
     Color space conversion may also utilize filtering, i.e., taking samples from a kernel around a pixel and applying a weighted interpolation. Filtering is used to preserve image quality when sampling in a non-direct manner (e.g., a non-one-to-one manner) from an image. Moreover, filtering is common if the image is used as part of an image processing pipeline that may apply scaling, rotations, or other arbitrary access. In some instances, filtering may need samples to be in a linear space. 
     Gamma space filtering may have been originally utilized with non-linear monitor intensity (e.g., in cathode ray tube (CRT) monitors). More recently, gamma space filtering may be utilized so humans can determine the difference between darker shades better than lighter shades. For instance, in order to compress an image into a limited dynamic range (e.g., a bit depth range), linear images may be converted to gamma. A typical use for video and data may send these results to a display (e.g., modern displays may convert back to linear space). There may also be various types of gamma spaces, such that some gamma spaces are more complex than a certain amount (e.g., X 0.45 ). 
     In some aspects, combining-based image calculations (e.g., interpolative filtering, sampling, blending, etc.) may not work in a non-linear gamma space. For example, filtering may make the end result (i.e., after de-gamma) darker than intended. For instance, a key artifact may be that gamma space filtering is not ‘energy’ preserving. Moreover, the amount the end results gets darker may depend on the sample position. 
       FIG.  4    includes diagrams  400 ,  410 ,  420 ,  430 , and  440  illustrating an example linear sampling process and an example gamma space filtering process. More specifically, diagrams  400 ,  410 ,  420 ,  430 , and  440  depict a sampling example of comparing a linear sampling process to a gamma space filtering process. As shown in  FIG.  4   , diagrams  400 ,  410 ,  420 ,  430 , and  440  show a simplified linear sampling performed at the black ‘x’. For instance, as the sampling process moves along (i.e., the black cross moves to the right), the amount of linear sampling is adjusted in a linear fashion. As further shown in  FIG.  4   , for gamma space filtering, the sampling is too dark in diagrams  410 ,  420 , and  430 . 
     Some aspects of color space conversion may have difficulty filtering in a non-linear space. For example, after an RGB image is generated, in order to preserve bit-rate, the RGB image may be non-linearly (gamma) compressed. The non-linear RGB may be converted to YUV for video encoding and transfer. On the receiving end, the image may be used as part of an image processing pipeline. This process may need filtering, but the YUV image may internally contain non-linear data. The correct sequence may need the YUV image to be converted to non-linear RGB, and then converted to linear RGB before filtering. For arbitrary pixel access, this sequence may be computationally intense and may not be directly supported by hardware. 
     In addition to difficulty filtering in a non-linear space, some aspects of color space conversion may have difficulty converting to a linear space. In some instances, a non-linear YUV source may originate from a high dynamic range RGB. Also, the non-linear YUV source may be compressed to a lower bit rate non-linear (gamma) sRGB to conserve bandwidth. Further, the non-linear YUV source may be converted to YUV (e.g., YUV4:2:0 or NV12) for further chroma sub-sampling compression. In a traditional access, a conversion from non-linear YUV to sRGB and/or high dynamic range linear RGB may be performed by inverting the source generation process on a per-pixel basis. The traditional access may be typically performed for the source image as a whole (e.g., no scaling or image manipulation). Also, the traditional access may not utilize the non-linear combination of pixels. An arbitrary non-linear YUV access may be an arbitrary pixel access (e.g., scaling, rotation, or other image processing) that may utilize filtering multiple samples together. In arbitrary pixel access, the filtering may need to occur in a linear space. Also, the conversion of non-linear YUV samples to linear space may be complex and difficult to implement efficiently in hardware or software. 
       FIGS.  5 A and  5 B  include diagrams  500  and  550 , respectively, illustrating example non-linear YUV encoding processes. More specifically, diagram  500  depicts non-linear YUV encoding process for non-constant luminance (NCL), and diagram  550  depicts non-linear YUV encoding process for constant luminance (CL). As shown in  FIG.  5 A , diagram  500  includes NCL encoding process  510  including color components  512  (e.g., R, G, B), non-linear components  514  (e.g., Y′, U′, V′), gamma compression  518 , color space conversion  520 , and downsample process  522 .  FIG.  5 A  also shows that certain aspects of the NCL encoding process  510  may result in incorrect calculations as they are applied in non-linear color space. As shown in  FIG.  5 B , diagram  550  includes CL encoding process  560  including color components  562  (e.g., R, G, B), non-linear components  564  (e.g., Y′, U′, V′), gamma compression  568 , color space conversion  570 , and downsample process  572 .  FIG.  5 B  also shows that certain aspects of the CL encoding process  560  may result in incorrect calculations as they are applied in non-linear color space. 
     As shown in  FIGS.  5 A and  5 B , a non-linear YUV encoding process may include a gamma space compression, which may convert a high dynamic range RGB to a lower bitrate sRGB. The sRGB may include non-linear R′, G′, and B′ components. The gamma space compression may also allow storage of an intermediate image. As further shown in  FIGS.  5 A and  5 B , the non-linear YUV encoding process may include a color space conversion  520  and  570 , such that the non-linear sRGB (e.g., R′G′B′) may be converted to a non-linear YUV (e.g., Y′U′V′). There may additionally be chroma sub-sampling. As further shown in  FIGS.  5 A and  5 B , a convenience of early gamma space compression in non-linear YUV encoding process may be the ability to store the intermediate lower bitrate sRGB image. One disadvantage of a non-linear YUV encoding process is that the color space conversion and sub-sampling operations may use non-linear values. 
       FIGS.  6 A and  6 B  include diagrams  600  and  650 , respectively, illustrating example non-linear YUV decoding processes. More specifically, diagram  600  depicts non-linear YUV decoding process for non-constant luminance (NCL), and diagram  650  depicts non-linear YUV decoding process for constant luminance (CL). As shown in  FIG.  6 A , diagram  600  includes NCL decoding process  610  including color components  612  (e.g., R, G, B), non-linear components  614  (e.g., Y′, U′, V′), upsample process  618 , color space conversion  620 , and de-gamma process  622 .  FIG.  6 A  also shows that certain aspects of the NCL decoding process  610  may result in incorrect calculations as they are applied in non-linear color space. As shown in  FIG.  6 B , diagram  650  includes CL decoding process  660  including color components  662  (e.g., R, G, B), non-linear components  664  (e.g., Y′, U′, V′), upsample process  668 , color space conversion  670 , and de-gamma process  672 .  FIG.  6 B  also shows that certain aspects of the CL decoding process  660  may result in incorrect calculations as they are applied in non-linear color space. 
     As shown in  FIGS.  6 A and  6 B , a non-linear YUV decoding process may include chroma up-sampling. The non-linear YUV decoding process may also include a color space conversion  620  and  670 , such that the non-linear YUV (e.g., Y′U′V′) may be converted to an sRGB (e.g., R′G′B′). Further, the non-linear YUV decoding process may include a de-gamma process  622  and  672 , such that the sRGB (e.g., R′G′B′) may be converted to a high dynamic range RGB. One disadvantage of a non-linear YUV decoding process is that up-sampling and color space conversion operations may use non-linear values. 
       FIGS.  7 A and  7 B  include diagrams  700  and  750 , respectively, illustrating example non-linear YUV decoding processes with filtering. More specifically, diagram  700  depicts non-linear YUV decoding process with filtering for non-constant luminance (NCL), and diagram  750  depicts non-linear YUV decoding process with filtering for constant luminance (CL). As shown in  FIG.  7 A , diagram  700  includes NCL decoding process with filtering  710  including color components  712  (e.g., R, G, B), non-linear components  714  (e.g., Y′, U′, V′), filter process  716 , upsample process  718 , color space conversion  720 , and de-gamma process  722 .  FIG.  7 A  also shows that certain aspects of the NCL decoding process with filtering  710  may result in incorrect calculations as they are applied in non-linear color space. Also, filter process  716  may include more serious incorrect calculations that are applied in non-linear color space compared to incorrect calculations in other parts of the pipeline. As shown in  FIG.  7 B , diagram  750  includes CL decoding process with filtering  760  including color components  762  (e.g., R, G, B), non-linear components  764  (e.g., Y′, U′, V′), filter process  766 , upsample process  768 , color space conversion  770 , and de-gamma process  772 .  FIG.  7 B  also shows that certain aspects of the CL decoding process with filtering  760  may result in incorrect calculations as they are applied in non-linear color space. Also, filter process  766  may include more serious incorrect calculations that are applied in non-linear color space compared to incorrect calculations in other parts of the pipeline. 
     As shown in  FIGS.  7 A and  7 B , a non-linear YUV decoding process with filtering may include filter process  716  and  766  that can filter multiple samples together. However, this filter process may result in significant error due to non-linear values. The non-linear YUV decoding process with filtering  710  and  760  may also include chroma sub-sampling, which may result in some error due to non-linear values. The non-linear YUV decoding process with filtering  710  and  760  may also include color space conversion, which may result in some error when converting non-linear YUV (Y′U′ V′) to sRGB (e.g., R′G′B′). Further, the non-linear YUV decoding process with filtering  710  and  760  may include de-gamma process  722  and  772 , which may convert sRGB to high dynamic range RGB. In some aspects, hardware pipelines may typically filter before applying more complex color processing operations. One disadvantage of a non-linear YUV decoding process with filtering is that up-sampling and color space conversion operations may utilize non-linear values. 
     Based on the above, it may be beneficial for non-linear YUV conversion processes to filter in a non-linear space. It may also be beneficial to convert to a linear space during a non-linear YUV conversion process. For instance, it may be beneficial to convert non-linear YUV samples to a linear space during a non-linear YUV conversion process. Further, it may be beneficial for non-linear YUV conversion processes to utilize up-sampling and color space conversion operations with non-linear values. 
     Aspects of the present disclosure may include non-linear YUV conversion processes that filter in a non-linear space. Also, aspects of the present disclosure may convert to a linear space during a non-linear YUV conversion process. For instance, aspects of the present disclosure may convert non-linear YUV samples to a linear space during a non-linear YUV conversion process. Additionally, in some instances, aspects of the present disclosure may include non-linear YUV conversion processes that utilize up-sampling and color space conversion operations with non-linear values. Aspects of the present disclosure may also move the non-linear compression from individual channels (e.g., R, G, B channels) to a certain channel (e.g., a luma (Y) channel) after a color space conversion (e.g., an RGB-to-YUV conversion). By doing so, aspects of the present disclosure may preserve the nature of non-linear luma compression while making it easier to sample, convert to linear components, and/or filter in a YUV space. Additionally, aspects of the present disclosure may allow certain video formats to remain unaffected, such as an intermediate YUV 4:2:0 video format (e.g., NV12). 
     Additionally, aspects of the present disclosure may include non-linear YUV conversion processes with solely a luma/luminance (Y/Y′) component. As such, aspects of the present disclosure may provide non-linear YUV conversion processes for a luma/luminance (Y/Y′) channel, i.e., without chroma/chrominance (UV/U′V′) channels. For instance, aspects of the present disclosure may utilize a non-linear YUV encoding process for the luma/luminance component or channel. Aspects of the present disclosure may also utilize a non-linear YUV decoding process for the luma/luminance component or channel. Moreover, aspects of the present disclosure may also utilize a non-linear YUV decoding process with filtering for the luma/luminance component or channel. 
       FIG.  8    includes diagram  800  illustrating an example non-linear YUV encoding process. More specifically, diagram  800  depicts non-linear YUV encoding process for a luma/luminance (Y/Y′) component. As shown in  FIG.  8   , diagram  800  includes Y-only encoding process  810  including color components  812  (e.g., R, G, B), non-linear components  814  (e.g., Y′, U′, V′), gamma compression  818 , color space conversion  820 , and downsample process  822 .  FIG.  8    also shows that aspects of the Y-only encoding process  810  may not result in any step corresponding to an incorrect color space. Accordingly, the Y-only encoding process  810  may result in each step in the process performed correctly in linear color space. 
     As shown in  FIG.  8   , a non-linear YUV encoding process with solely a luma/luminance (Y/Y′) component may include a color space conversion  820 , such that the linear RGB may be converted to a linear YUV.  FIG.  8    may also include a gamma space compression of solely the Y channel. As such, the gamma space compression in the non-linear YUV encoding process with solely a Y channel may not be performed on the UV channels. The non-linear YUV encoding process with solely a luma/luminance (Y/Y′) component may additionally include chroma sub-sampling with the use of linear components. As further shown in  FIG.  8   , all of the color processing in Y-only encoding process  810  may be performed on linear components. Alternatively, for an sRGB (R′G′B′) source, the Y-only encoding process may include R′G′B′ inputs and a de-gamma process that is performed on each channel immediately after the R′G′B′ inputs. 
       FIG.  9    includes diagram  900  illustrating an example non-linear YUV decoding process. More specifically, diagram  900  depicts non-linear YUV decoding process for a luma/luminance (Y/Y′) component. As shown in  FIG.  9   , diagram  900  includes Y-only decoding process  910  including color components  912  (e.g., R, G, B), non-linear components  914  (e.g., Y′, U′, V′), upsample process  918 , color space conversion  920 , and de-gamma process  922 .  FIG.  9    also shows that aspects of the Y-only decoding process  910  may not result in any step with calculations in an incorrect non-linear color space. Thus, the Y-only decoding process  910  may result in each step in the process performed correctly in linear color space. 
     As shown in  FIG.  9   , a non-linear YUV decoding process with solely a luma/luminance (Y/Y′) component may include a color space conversion  920  from YUV to RGB, such that the linear YUV may be converted to RGB.  FIG.  9    shows that Y-only decoding process  910  may include a chroma up-sampling process (e.g., upsample process  918 ). For instance, the non-linear YUV decoding process with solely a luma/luminance (Y/Y′) component may additionally include chroma sub-sampling with the use of linear components. As further shown in  FIG.  9   , all of the color processing in Y-only decoding process  910  may be performed in a linear space. Further, as shown in  FIG.  9   , the de-gamma process of samples may be supported in hardware. 
       FIG.  10    includes diagram  1000  illustrating an example non-linear YUV decoding process with filtering. More specifically, diagram  1000  depicts non-linear YUV decoding process with filtering for a luma/luminance (Y/Y′) component. As shown in  FIG.  10   , diagram  1000  includes Y-only decoding process with filtering  1010  including color components  1012  (e.g., R, G, B), non-linear components  1014  (e.g., Y′, U′, V′), filter process  1016 , upsample process  1018 , color space conversion  1020 , and de-gamma process  1022 . Further, diagram  1000  in  FIG.  10    includes a GPU texture processor (TP) processing portion  1030  and a GPU shader processor (SP) processing portion  1040 . Accordingly, a portion of Y-only decoding process with filtering  1010  may be processed at the TP of the GPU (e.g., GPU TP processing portion  1030 ) and another portion of Y-only decoding process with filtering  1010  may be processed at the SP of the GPU (e.g., GPU SP processing portion  1040 ).  FIG.  10    also shows that aspects of the Y-only decoding process with filtering  1010  may not result in any step with calculations in an incorrect non-linear color space. Accordingly, the Y-only decoding process with filtering  1010  may result in each step in the process performed correctly in linear color space. 
     As shown in  FIG.  10   , a non-linear YUV decoding process with filtering including solely a luma/luminance (Y/Y′) component may include a color space conversion  1020  from YUV to RGB, such that the linear YUV may be converted to RGB.  FIG.  10    shows that Y-only decoding process with filtering  1010  may include filtering multiple samples together (e.g., via filter process  1016 ). As such, the non-linear YUV decoding process with filtering including solely a Y channel may perform a Y-channel de-gamma process on all samples before filtering. The non-linear YUV decoding process with filtering including solely a luma/luminance (Y/Y′) component may additionally include chroma sub-sampling with the use of linear components. As further shown in  FIG.  10   , all of the color processing in Y-only decoding process with filtering  1010  may be performed in a linear space. Further, as shown in  FIG.  10   , the de-gamma of samples may be supported in hardware before filtering. 
     In some aspects of filtering for a non-linear YUV conversion at a GPU, TP filtering may be forced on non-linear values. This may result in non-linear errors being propagated throughout the TP and SP processing. In contrast, aspects of the present disclosure may include a non-linear YUV conversion with TP filtering on solely linear values. Accordingly, aspects of the present disclosure may provide accurate values, such that no errors are propagated throughout the TP and SP processing. Aspects of the present disclosure may also allow for all of the TP and SP processing at a GPU to be performed on linear values. Further, aspects of the present disclosure may perform a de-gamma process of Y samples before filtering. In some instances, this may be supported by TP hardware. 
     Aspects of the present disclosure may include a number of benefits or advantages. For instance, aspects of the present disclosure may propagate accurate values throughout TP and SP processing. Aspects of the present disclosure may also move the non-linear compression from individual channels (e.g., R, G, B channels) to a certain channel (e.g., a luma (Y) channel) after a color space conversion (e.g., an RGB-to-YUV conversion). By doing so, aspects of the present disclosure may preserve the nature of non-linear luma compression while making it easier to sample, convert to linear components, and/or filter in a YUV space. Additionally, aspects of the present disclosure may allow certain video formats to remain unaffected, such as an intermediate YUV 4:2:0 video format (e.g., NV12). 
       FIG.  11    is a communication flow diagram  1100  of graphics processing in accordance with one or more techniques of this disclosure. As shown in  FIG.  11   , diagram  1100  includes example communications between components of a GPU (or other graphics processor), e.g., GPU component  1102 , GPU component  1104 , and GPU component  1106 , in accordance with one or more techniques of this disclosure. 
     At  1110 , GPU component  1102  may transmit a request for a plurality of pixels associated with a first color space (e.g., request  1112 ), where a plurality of pixels is received based on the transmitted request. The request may be transmitted from a shader processor of a graphics processing unit (GPU) to a texture processor of the GPU. 
     At  1120 , GPU component  1102  may receive a plurality of pixels associated with a first color space including a plurality of first color channels (e.g., pixels  1122 ), at least one first color channel of the plurality of first color channels being a first compressed channel. The first color space may be a luminance (Y) chrominance (UV) (YUV) color space and the second color space may be a red (R) green (G) blue (B) (RGB) color space. 
     At  1130 , GPU component  1102  may read the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel. 
     At  1140 , GPU component  1102  may decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. The decompression of the at least one first channel may be a non-linear decompression, such that the decompression converts the at least one first channel from a non-linear channel to a linear channel. Also, one or more first channels of the plurality of first color channels may be linear channels, such that the one or more first channels are not decompressed. In some instances, the at least one first color channel may be non-linearly compressed prior to being decompressed. 
     At  1150 , GPU component  1102  may filter each of the plurality of first color channels after the at least one first color channel is decompressed. Each of the plurality of first color channels may be linearly filtered, bi-linearly filtered, or non-linearly filtered. 
     At  1160 , GPU component  1102  may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels. The color space conversion may be simultaneously performed for each of the plurality of first color channels. Also, the color space conversion may be performed in at least one of a texture processor of a graphics processing unit (GPU) or a shader processor of the GPU. In some aspects, GPU component  1102  may combine the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. For instance, performing the color space conversion of the first color space may further include combining the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. The combination of the at least one first channel with the at least one other first channel and the at least one additional first channel may be performed by a matrix combiner. 
     At  1170 , GPU component  1102  may transmit the plurality of pixels associated with the second color space (e.g., pixels  1172 ) after the color space conversion. The plurality of pixels may be transmitted to a shader processor of a graphics processing unit (GPU). 
       FIG.  12    is a flowchart  1200  of an example method of graphics processing in accordance with one or more techniques of this disclosure. The method may be performed by a GPU, such as an apparatus for graphics processing, a graphics processor, a wireless communication device, and/or any apparatus that may perform graphics processing as used in connection with the examples of  FIGS.  1 - 11   . The methods described herein may provide a number of benefits, such as improving resource utilization and/or power savings. 
     At  1204 , the GPU may receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1120  of  FIG.  11   , GPU component  1102  may receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel. Further, step  1204  may be performed by processing unit  120  in  FIG.  1   . The first color space may be a luminance (Y) chrominance (UV) (YUV) color space and the second color space may be a red (R) green (G) blue (B) (RGB) color space. 
     At  1208 , the GPU may decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1140  of  FIG.  11   , GPU component  1102  may decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. Further, step  1208  may be performed by processing unit  120  in  FIG.  1   . The decompression of the at least one first channel may be a non-linear decompression, such that the decompression converts the at least one first channel from a non-linear channel to a linear channel. Also, one or more first channels of the plurality of first color channels may be linear channels, such that the one or more first channels are not decompressed. In some instances, the at least one first color channel may be non-linearly compressed prior to being decompressed. 
     At  1212 , the GPU may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1160  of  FIG.  11   , GPU component  1102  may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels. Further, step  1212  may be performed by processing unit  120  in  FIG.  1   . The color space conversion may be simultaneously performed for each of the plurality of first color channels. Also, the color space conversion may be performed in at least one of a texture processor of a graphics processing unit (GPU) or a shader processor of the GPU. In some aspects, GPU component  1102  may combine the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. For instance, performing the color space conversion of the first color space may further include combining the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. The combination of the at least one first channel with the at least one other first channel and the at least one additional first channel may be performed by a matrix combiner. 
       FIG.  13    is a flowchart  1300  of an example method of graphics processing in accordance with one or more techniques of this disclosure. The method may be performed by a GPU, such as an apparatus for graphics processing, a graphics processor, a wireless communication device, and/or any apparatus that may perform graphics processing as used in connection with the examples of  FIGS.  1 - 11   . The methods described herein may provide a number of benefits, such as improving resource utilization and/or power savings. 
     At  1302 , the GPU may transmit a request for a plurality of pixels associated with a first color space, where a plurality of pixels is received based on the transmitted request, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1110  of  FIG.  11   , GPU component  1102  may transmit a request for a plurality of pixels associated with a first color space, where a plurality of pixels is received based on the transmitted request. Further, step  1302  may be performed by processing unit  120  in  FIG.  1   . The request may be transmitted from a shader processor of a graphics processing unit (GPU) to a texture processor of the GPU. 
     At  1304 , the GPU may receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1120  of  FIG.  11   , GPU component  1102  may receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel. Further, step  1304  may be performed by processing unit  120  in  FIG.  1   . The first color space may be a luminance (Y) chrominance (UV) (YUV) color space and the second color space may be a red (R) green (G) blue (B) (RGB) color space. 
     At  1306 , the GPU may read the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1130  of  FIG.  11   , GPU component  1102  may read the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel. Further, step  1306  may be performed by processing unit  120  in  FIG.  1   . 
     At  1308 , the GPU may decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1140  of  FIG.  11   , GPU component  1102  may decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel. Further, step  1308  may be performed by processing unit  120  in  FIG.  1   . The decompression of the at least one first channel may be a non-linear decompression, such that the decompression converts the at least one first channel from a non-linear channel to a linear channel. Also, one or more first channels of the plurality of first color channels may be linear channels, such that the one or more first channels are not decompressed. In some instances, the at least one first color channel may be non-linearly compressed prior to being decompressed. 
     At  1310 , the GPU may filter each of the plurality of first color channels after the at least one first color channel is decompressed, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1150  of  FIG.  11   , GPU component  1102  may filter each of the plurality of first color channels after the at least one first color channel is decompressed. Further, step  1310  may be performed by processing unit  120  in  FIG.  1   . Each of the plurality of first color channels may be linearly filtered, bi-linearly filtered, or non-linearly filtered. 
     At  1312 , the GPU may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1160  of  FIG.  11   , GPU component  1102  may perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels. Further, step  1312  may be performed by processing unit  120  in  FIG.  1   . The color space conversion may be simultaneously performed for each of the plurality of first color channels. Also, the color space conversion may be performed in at least one of a texture processor of a graphics processing unit (GPU) or a shader processor of the GPU. In some aspects, GPU component  1102  may combine the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. For instance, performing the color space conversion of the first color space may further include combining the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. The combination of the at least one first channel with the at least one other first channel and the at least one additional first channel may be performed by a matrix combiner. 
     At  1314 , the GPU may transmit the plurality of pixels associated with the second color space after the color space conversion, as described in connection with the examples in  FIGS.  1 - 11   . For example, as described in  1170  of  FIG.  11   , GPU component  1102  may transmit the plurality of pixels associated with the second color space after the color space conversion. Further, step  1314  may be performed by processing unit  120  in  FIG.  1   . The plurality of pixels may be transmitted to a shader processor of a graphics processing unit (GPU). 
     In configurations, a method or an apparatus for graphics processing is provided. The apparatus may be a GPU, a graphics processor, or some other processor that may perform graphics processing. In aspects, the apparatus may be the processing unit  120  within the device  104 , or may be some other hardware within the device  104  or another device. The apparatus, e.g., processing unit  120 , may include means for receiving a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel; means for decompressing the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel; means for performing a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels; means for combining the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels; means for filtering each of the plurality of first color channels after the at least one first color channel is decompressed; means for reading the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel; means for transmitting a request for the plurality of pixels associated with the first color space, where the plurality of pixels is received based on the transmitted request; and means for transmitting the plurality of pixels associated with the second color space after the color space conversion. 
     The subject matter described herein may be implemented to realize one or more benefits or advantages. For instance, the described graphics processing techniques may be used by a GPU, a graphics processor, or some other processor that may perform graphics processing to implement the non-linear filtering techniques described herein. This may also be accomplished at a low cost compared to other graphics processing techniques. Moreover, the graphics processing techniques herein may improve or speed up data processing or execution. Further, the graphics processing techniques herein may improve resource or data utilization and/or resource efficiency. Additionally, aspects of the present disclosure may utilize non-linear filtering techniques in order to improve memory bandwidth efficiency and/or increase processing speed at a GPU. 
     It is understood that the specific order or hierarchy of blocks in the processes/flowcharts disclosed is an illustration of example approaches. Based upon design preferences, it is understood that the specific order or hierarchy of blocks in the processes/flowcharts may be rearranged. Further, some blocks may be combined or omitted. The accompanying method claims present elements of the various blocks in a sample order, and are not meant to be limited to the specific order or hierarchy presented. 
     The previous description is provided to enable any person skilled in the art to practice the various aspects described herein. Various modifications to these aspects will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other aspects. Thus, the claims are not intended to be limited to the aspects shown herein, but is to be accorded the full scope consistent with the language of the claims, wherein reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” The word “exemplary” is used herein to mean “serving as an example, instance, or illustration.” Any aspect described herein as “exemplary” is not necessarily to be construed as preferred or advantageous over other aspects. 
     Unless specifically stated otherwise, the term “some” refers to one or more and the term “or” may be interpreted as “and/or” where context does not dictate otherwise. Combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” include any combination of A, B, and/or C, and may include multiples of A, multiples of B, or multiples of C. Specifically, combinations such as “at least one of A, B, or C,” “one or more of A, B, or C,” “at least one of A, B, and C,” “one or more of A, B, and C,” and “A, B, C, or any combination thereof” may be A only, B only, C only, A and B, A and C, B and C, or A and B and C, where any such combinations may contain one or more member or members of A, B, or C. All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims. The words “module,” “mechanism,” “element,” “device,” and the like may not be a substitute for the word “means.” As such, no claim element is to be construed as a means plus function unless the element is expressly recited using the phrase “means for.” 
     In one or more examples, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. For example, although the term “processing unit” has been used throughout this disclosure, such processing units may be implemented in hardware, software, firmware, or any combination thereof. If any function, processing unit, technique described herein, or other module is implemented in software, the function, processing unit, technique described herein, or other module may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. 
     In accordance with this disclosure, the term “or” may be interpreted as “and/or” where context does not dictate otherwise. Additionally, while phrases such as “one or more” or “at least one” or the like may have been used for some features disclosed herein but not others, the features for which such language was not used may be interpreted to have such a meaning implied where context does not dictate otherwise. 
     In one or more examples, the functions described herein may be implemented in hardware, software, firmware, or any combination thereof. For example, although the term “processing unit” has been used throughout this disclosure, such processing units may be implemented in hardware, software, firmware, or any combination thereof. If any function, processing unit, technique described herein, or other module is implemented in software, the function, processing unit, technique described herein, or other module may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media may include computer data storage media or communication media including any medium that facilitates transfer of a computer program from one place to another. In this manner, computer-readable media generally may correspond to (1) tangible computer-readable storage media, which is non-transitory or (2) a communication medium such as a signal or carrier wave. Data storage media may be any available media that may be accessed by one or more computers or one or more processors to retrieve instructions, code and/or data structures for implementation of the techniques described in this disclosure. By way of example, and not limitation, such computer-readable media may comprise RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices. Disk and disc, as used herein, includes compact disc (CD), laser disc, optical disc, digital versatile disc (DVD), floppy disk and Blu-ray disc where disks usually reproduce data magnetically, while discs reproduce data optically with lasers. Combinations of the above should also be included within the scope of computer-readable media. A computer program product may include a computer-readable medium. 
     The code may be executed by one or more processors, such as one or more digital signal processors (DSPs), general purpose microprocessors, application specific integrated circuits (ASICs), arithmetic logic units (ALUs), field programmable logic arrays (FPGAs), or other equivalent integrated or discrete logic circuitry. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described herein. Also, the techniques could be fully implemented in one or more circuits or logic elements. 
     The techniques of this disclosure may be implemented in a wide variety of devices or apparatuses, including a wireless handset, an integrated circuit (IC) or a set of ICs, e.g., a chip set. Various components, modules or units are described in this disclosure to emphasize functional aspects of devices configured to perform the disclosed techniques, but do not necessarily need realization by different hardware units. Rather, as described above, various units may be combined in any hardware unit or provided by a collection of inter-operative hardware units, including one or more processors as described above, in conjunction with suitable software and/or firmware. Accordingly, the term “processor,” as used herein may refer to any of the foregoing structure or any other structure suitable for implementation of the techniques described herein. Also, the techniques may be fully implemented in one or more circuits or logic elements. 
     The following aspects are illustrative only and may be combined with other aspects or teachings described herein, without limitation. 
     Aspect 1 is an apparatus for graphics processing including at least one processor coupled to a memory and configured to: receive a plurality of pixels associated with a first color space including a plurality of first color channels, at least one first color channel of the plurality of first color channels being a first compressed channel; decompress the at least one first color channel of the plurality of first color channels, the at least one first color channel being decompressed from the first compressed channel to a first decompressed channel; and perform a color space conversion of the first color space associated with the plurality of pixels, such that the plurality of first color channels is converted to a plurality of second color channels, the plurality of second color channels being associated with a second color space for the plurality of pixels. 
     Aspect 2 is the apparatus of aspect 1, where the decompression of the at least one first channel is a non-linear decompression, such that the decompression converts the at least one first channel from a non-linear channel to a linear channel. 
     Aspect 3 is the apparatus of any of aspects 1 and 2, where one or more first channels of the plurality of first color channels are linear channels, such that the one or more first channels are not decompressed. 
     Aspect 4 is the apparatus of any of aspects 1 to 3, where to perform the color space conversion of the first color space, the at least one processor is configured to: combine the at least one first channel with at least one other first channel of the plurality of first color channels and at least one additional first channel of the plurality of first color channels. 
     Aspect 5 is the apparatus of any of aspects 1 to 4, where the combination of the at least one first channel with the at least one other first channel and the at least one additional first channel is performed by a matrix combiner. 
     Aspect 6 is the apparatus of any of aspects 1 to 5, where the at least one processor is further configured to: filter each of the plurality of first color channels after the at least one first color channel is decompressed. 
     Aspect 7 is the apparatus of any of aspects 1 to 6, where each of the plurality of first color channels is linearly filtered, bi-linearly filtered, or non-linearly filtered. 
     Aspect 8 is the apparatus of any of aspects 1 to 7, where the at least one first color channel is non-linearly compressed prior to being decompressed. 
     Aspect 9 is the apparatus of any of aspects 1 to 8, where the at least one processor is further configured to: read the plurality of pixels associated with the first color space including the plurality of first color channels, where the plurality of pixels is read prior to decompressing the at least one first color channel. 
     Aspect 10 is the apparatus of any of aspects 1 to 9, where the at least one processor is further configured to: transmit a request for the plurality of pixels associated with the first color space, where the plurality of pixels is received based on the transmitted request. 
     Aspect 11 is the apparatus of any of aspects 1 to 10, where the request is transmitted from a shader processor of a graphics processing unit (GPU) to a texture processor of the GPU. 
     Aspect 12 is the apparatus of any of aspects 1 to 11, where the at least one processor is further configured to: transmit the plurality of pixels associated with the second color space after the color space conversion. 
     Aspect 13 is the apparatus of any of aspects 1 to 12, where the plurality of pixels is transmitted to a shader processor of a graphics processing unit (GPU). 
     Aspect 14 is the apparatus of any of aspects 1 to 13, where the first color space is a luminance (Y) chrominance (UV) (YUV) color space and the second color space is a red (R) green (G) blue (B) (RGB) color space. 
     Aspect 15 is the apparatus of any of aspects 1 to 14, where the color space conversion is simultaneously performed for each of the plurality of first color channels. 
     Aspect 16 is the apparatus of any of aspects 1 to 15, where the color space conversion is performed in at least one of a texture processor of a graphics processing unit (GPU) or a shader processor of the GPU. 
     Aspect 17 is the apparatus of any of aspects 1 to 16, where the apparatus is a wireless communication device, further including at least one of an antenna or a transceiver coupled to the at least one processor. 
     Aspect 18 is a method of graphics processing for implementing any of aspects 1 to 17. 
     Aspect 19 is an apparatus for graphics processing including means for implementing any of aspects 1 to 17. 
     Aspect 20 is a computer-readable medium storing computer executable code, the code when executed by at least one processor causes the at least one processor to implement any of aspects 1 to 17.