Patent Publication Number: US-8994845-B2

Title: System and method of adjusting a camera based on image data

Description:
FIELD OF TECHNOLOGY 
     The subject matter herein generally relates to mobile devices, and more specifically relates to a system and method of adjusting camera image data captured by mobile device cameras. 
     BACKGROUND 
     With the advent of more robust electronic systems, advancements of mobile devices are becoming more prevalent. Mobile devices can provide a variety of functions including, for example, telephonic, audio/video, and gaming functions. Mobile devices can include mobile stations such as cellular telephones, smart telephones, portable gaming systems, portable audio and video players, electronic writing or typing tablets, handheld messaging devices, personal digital assistants, and handheld computers. 
     Mobile devices allow users to have an integrated device which can perform a variety of different tasks. For example, a mobile device can be enabled for each of or some of the following functions: voice transmission (cell phones), text transmission (pagers and PDAs), sending and receiving data for viewing of Internet websites and multi-media messages. Additionally, mobile devices can include one or more applications such as a camera application for capturing photographs or videos. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       Implementations of the present technology will now be described, by way of example only, with reference to the attached figures, wherein: 
         FIG. 1  is an illustration of a rear view of an example mobile device having a visible light camera module and a non-visible light camera module in accordance with an example implementation of the present technology; 
         FIG. 2  is a block diagram of an example mobile device configured for adjusting camera image data in accordance with an example implementation of the present technology; 
         FIG. 3  is a block diagram of a portion of a system for adjusting camera image data in accordance with an example implementation of the present technology, including a memory device; 
         FIG. 4  is an illustration of a memory device having portions for non-visible light camera image data, visible light camera image data, and hybrid image data in accordance with an example implementation of the present technology; 
         FIG. 5  is an illustration of a memory device having portions for non-visible light camera image data, visible light camera image data, and hybrid image data in accordance with an example implementation of the present technology, with image data stored in the memory device; 
         FIG. 6A  is an illustration of a visible light camera image in accordance with an example implementation of the present technology; 
         FIG. 6B  is an illustration of a non-visible light camera image in accordance with an example implementation of the present technology; 
         FIG. 7A  is an illustration of a visible light camera image in accordance with an example implementation of the present technology, illustrating the contour of an object in the image; 
         FIG. 7B  is an illustration of a non-visible light camera image in accordance with an example implementation of the present technology, illustrating the contour of an object in the image; 
         FIG. 8A  is an illustration of a visible light camera image in accordance with an example implementation of the present technology, illustrating the determination of the location of the portion of the image that does not meet a predetermined threshold associated with an acceptable quality factor of an image relative to a contour of the image; 
         FIG. 8B  is an illustration of a non-visible light camera image in accordance with an example implementation of the present technology, illustrating the determination of a portion of the non-visible light image corresponding to the portion of the visible light image illustrated in  FIG. 8A  that does not meet a predetermined threshold associated with an acceptable quality factor of an image; 
         FIG. 9  illustrates a hybrid image of the visible light image of  FIG. 6A  and the non-visible light image of  FIG. 6B ; 
         FIG. 10  is a flow chart of a method of adjusting camera image data in accordance with an example implementation; 
         FIG. 11  is a flow chart of another method of adjusting camera image data in which a quality factor of the hybrid image is determined; 
         FIG. 12  is a flow chart of an example method of adjusting camera image data in which the contours of the non-visible light camera image data and the visible light camera image data are determined to locate the portion(s) of the visible light camera image data that do not meet a predetermined threshold associated with an acceptable quality factor for images; and 
         FIG. 13  is an illustration of a front view of an example mobile device wherein an exemplary camera setting menu, in which augmentation or adjusting of camera image data can be user-selected or user-defined, is shown on the display. 
     
    
    
     DETAILED DESCRIPTION 
     For simplicity and clarity of illustration, where appropriate, reference numerals have been repeated among the different figures to indicate corresponding or analogous elements. In addition, numerous specific details are set forth in order to provide a thorough understanding of the implementations described herein. However, those of ordinary skill in the art will understand that the implementations described herein can be practiced without these specific details. In other instances, methods, procedures and components have not been described in detail so as not to obscure the related relevant feature being described. Also, the disclosure is not to be considered as limiting the scope of the implementations described herein. 
     Several definitions that apply throughout this disclosure will now be presented. The word “coupled” is defined as connected, whether directly or indirectly through intervening components, and is not necessarily limited to physical connections. The term “communicatively coupled” is defined as connected whether directly or indirectly through intervening components, is not necessarily limited to a physical connection, and allows for the transfer of data. The term “mobile device” is defined as any electronic device that is capable of at least accepting information entries from a user and any electronic device that includes its own power source. “Wireless communication” means communication that occurs via an electromagnetic field between communicatively coupled devices. The term “memory” refers to transitory memory and non-transitory memory. For example, non-transitory memory can be implemented as Random Access Memory (RAM), Read-Only Memory (ROM), flash, ferromagnetic, phase-change memory, and other non-transitory memory technologies. A “histogram” is defined as a collection of a plurality of consecutive images (or image data) from a camera module. The histogram enables the construction of a history of a particular image using the previous images from the plurality of consecutive images in the histogram. “Dynamic range” as used herein describes the ability to capture objects in varying light conditions. A greater dynamic range allows for better capturing of images in light conditions that are dimmer and brighter than in a lesser dynamic range. “Dynamic range swing” as used herein refers to light conditions going from one extreme of the dynamic range to the other. 
     As mobile devices are compact, real estate within the mobile device is limited and compromises need to be made as to which components to include depending on the desired needs functions of the mobile device. With regard to mobile devices having cameras, the cameras typically have an infrared cut-off filter to allow the camera to capture color images. However, the filter blocks a significant percentage of light energy available in the scene which is being captured by the camera, thereby increasing the minimum light level required to generate an image. As a result, images captured on mobile device cameras tend to be darker. Additionally, as flashes on mobile device cameras require additional energy to power the flashes, lower-powered flashes are implemented, leading to a darker resultant image. As mobile devices having cameras require a higher minimum light level to generate an acceptable image, mobile device cameras are typically insufficient to capture nighttime images, indoor images, other low-light images, excessive light images, such as outdoor overly-sunlit images, or any other low-quality image. For example, in an environment in which there is full sun exposure or in an environment such as a darkroom both autofocus and fixed-focus lens cameras will produce substandard video output or substandard images. As the camera attempts to adjust or account for the lighting or lack thereof, the image processor will cycle through several settings in an attempt to find an optimum configuration for capturing images in such environments, thereby consuming excessive processing time, processing power, and battery life. Accordingly, the present disclosure provides a system and method of adjusting camera image data captured by a mobile device in an efficient manner. 
     The present disclosure provides for a system and method of adjusting camera image data. For example, the method of adjusting camera image data provides for detecting errors or poor image quality characteristics in an image captured by a visible light camera of a mobile device. The method of adjusting camera image data also provides for correcting for or eliminating such errors or poor image quality characteristics with a non-visible light camera image captured by a non-visible light camera of the mobile device by augmenting the low-quality image. While the present technology can operate or process image data, the present disclosure provides illustrations of the images associated with the image data to provide an illustration of the technology. In some embodiments, the intermediary images can be displayed, but in other embodiments no images are displayed until the image is fully processed, for example after being augmented. 
     In at least one implementation, the method of adjusting camera image data can include determining a quality factor of image data generated by a visible light camera module based on at least one predetermined characteristic; comparing the quality factor to a first predetermined threshold; augmenting the image data from the non-visible light camera module with image data generated by a non-visible light camera module to generate hybrid image data when the quality factor is below the first threshold. 
     For example, when an image is captured by a visible light camera of a mobile device, the quality of the image is analyzed. For example, a quality factor can be one or more of the following: the sharpness of the image, the lens exposure, the total exposure time, the luminance, color variations, whether there are any dead pixels (such as overexposed, underexposed, or unexposed pixels), or other quality characteristics of the image. In the example of a color variation, the determination can be made based on non-uniform colors, especially for regions that are outlines of shapes, and uniform flat regions and transition regions between two distinct color patterns. For example, when the quality factor is a color variation, a determination can be made that the quality of the image is acceptable if the image data from the visible light camera is above a threshold which in one example can be 95%. The example threshold of 95% can indicate the ability to track changing conditions via the visible light camera. In another example, image data passing the image quality level can be based on the type of lighting, for example, an indoor incandescent lighting or an outdoor daylight light spectrum. In one example, the image signal processor (ISP) can determine color uniformity for individual regions, pixels, groups of pixels, or use a look up table to scan the same region, pixels or group of pixels over a number of sequential images. Another quality factor can be “image signal to noise ratio.” 
     The quality factor of the image can be compared to a predetermined threshold (for example, a minimum sharpness level or value that is considered as an acceptable quality). In another example when a look up table is utilized, the determination of whether the quality factor is below a predetermined threshold can involve comparing the color component of the same pixel over a series of images to ensure that the color component is not changing. In another example, when the quality factor is an image signal to noise ratio, a determination is made as to whether the image is above a noise threshold (e.g., a noise floor). If the quality factor is at or below the predetermined threshold, a command can be sent to the non-visible light camera module of the mobile device to turn-on, activate, fully power or otherwise power the non-visible light camera module. For example, the non-visible light camera module can be activated when the visible light camera module is enabled but can be configured to enter into a low power mode when the non-visible light camera module is not needed. In other embodiments, the non-visible light camera module can be powered off until a determination is made that augmentation is required, and then the visible light camera module can enter a lower power mode, thereby further reducing power consumption. The low power mode can also be resumed between individual image data acquisition periods. 
     The non-visible light camera module can then be programmed and synchronized with the visible light camera such that when the visible light camera captures image data, the non-visible light camera will substantially simultaneously capture corresponding non-visible light image data. Alternatively, if the visible light camera and non-visible light camera acquire image data at different times, then an interpolation can be implemented to obtain an approximation of the image data at a given time. Alternatively, the image data from the visible light can be interpolated to be synchronized with the non-visible light camera data and then augmented. The visible light image data and the non-visible light image data can be combined with the non-visible light image data to form hybrid image data. The non-visible light image data can be combined with the visible light image data such that the quality of the hybrid image data has a quality factor that is at least equal to or greater than the predetermined threshold. Based on the quality of the hybrid image, the image sensor associated with the visible light camera can be adjusted, thereby ensuring that subsequent images captured by the visible light camera are of sufficient quality as compared to the predetermined threshold. In at least one implementation, after the hybrid image is formed or after the image sensor is adjusted, the non-visible light camera can be powered down, placed in an inactive state, placed in a standby state, or placed in any other low-powered state until a command or request is received in response to a determination that the visible light image data has a quality factor that is below the predetermined threshold, thereby conserving battery power, processing power, and image processing time. Moreover, as the quality factor of each image is analyzed and augmented or corrected as necessary, image data is dynamically augmented or corrected to provide images of acceptable quality. 
     Further details and examples of the present system and method of adjusting camera image data will now be discussed in relation to  FIGS. 1-13 . 
       FIG. 1  illustrates a view of a rear side  105  of an example mobile device  100  adapted to capture images in accordance with an example implementation. The illustrated mobile device  100  is a cellular phone but can also be a smartphone, a netbook, an electronic tablet, an electronic pad, a personal digital assistant (PDA), or any other similar electronic device which includes at least one camera module configured to capture images, such as still photo images, video images, or both still and video images. In  FIG. 1 , the mobile device  100  can include a visible light camera module  110  and a non-visible light camera module  115 . Also illustrated in  FIG. 1 , the mobile device  100  can include a flash  120 . Images sensed by the visible light camera module  110 , the non-visible light camera module  115 , or both the visible light camera module  110  and the non-visible light camera module  115  can be captured as photographs or videos. In one example, a camera application executed by a processor (not shown) is communicatively coupled to one or both of the visible light camera module  110  and the non-visible light camera module  115 . The flash  120  can provide light to assist in exposing the object or objects to be captured as a photograph or video by the visible light camera module  110  and the non-visible light camera module  115 . In other implementations, the flash  120 , the visible light camera module  110 , and the non-visible light camera module  115  can be located in different positions relative to one another as well as different positions on the backside of the mobile device  100 . In at least one implementation, the flash  120 , the visible light camera module  110  and the non-visible light camera module  115  can be located on the front side of the mobile device  100 . In another embodiment, the visible light camera module  110  and non-visible light camera module  115  can be implemented as a single module having one or more components. For example, one or more prisms, minors, or any combination thereof can be used to allow light received through a lens to be transferred to a visible light sensor and a non-visible light sensor. In other embodiments, filters can be implemented so that a single sensor type can be implemented. 
       FIG. 2  is a block diagram of an example mobile device  100  in accordance with an example implementation of the present disclosure. In  FIG. 2 , the mobile device  100  can include the visible light camera module  110  and a non-visible light module camera  115 . Each of the visible light camera module  110  and the non-visible light camera module  115  can be communicatively coupled to a processor, such as an image signal processor (ISP)  205 . In FIG.  2 , the visible light camera module  110  can include a camera lens (not shown). The visible camera module  110  can include an image sensor (not shown) that is adapted to convert the optical image captured by the visible camera module  110  into an electrical signal processed by the ISP  205 . The image sensor of the visible camera module  110  can be a charge-coupled device (CCD), complementary metal-oxide-semiconductor (CMOS), a hybrid CCD-CMOS image sensor, or any other sensor adapted to convert an optical image to an electrical signal. The visible light camera module  110  can allow visible light to pass through to the ISP  205 . For example, the visible light camera module  110  can filter the light so that it allows light having wavelengths from 400 nm-700 nm to reach the image sensor and to pass through to the ISP  205 . 
     Similarly, the non-visible light camera module  115  can include a non-visible light camera lens (not shown) for capturing non-visible light images of a scene. The non-visible light camera module  115  can be communicatively coupled to the image signal processor  205  to convert the image captured by the non-visible light camera module  115  into an electrical signal. The non-visible light camera module  115  can be an infrared camera module, a thermal camera module, a night vision camera module, an ultraviolet camera module, or any other camera module configured to capture images other than visible light images. For example, in an implementation where the non-visible light camera module is an infrared camera module, the infrared camera module can allow infrared (IR) light to pass through to the respective image sensor but can block all or most of the visible light spectrum of a scene or image. For example, the infrared camera module can allow light wavelengths from 700 nm-900 nm of the ambient light to reach the image sensor of the non-visible camera module through to the ISP  205 . 
     In  FIG. 2 , the ISP  205  can be a processor module dedicated to receiving image data from one or both of the visible light camera module  110  and the non-visible light camera module  115 . A processor as used herein can refer to a hardware processor such as an integrated circuit processor. The ISP  205  can be directly or indirectly coupled to the mobile device  100 . The ISP  205  can be a processor module including one or more processors. In other implementations, the ISP  205  can include one or more image signal processors. In at least one embodiment, the ISP  205  can be a single chip processor configured to analyze image data to determine a quality of the image data based on at least one predetermined characteristic (for example, sharpness, lens exposure time, total exposure time, luminance, whether a pixel of the image data is dead, or other characteristics of images). The ISP  205  can be further configured to transmit a request to the non-visible light camera module  115  to power on or otherwise change the powered state of the non-visible light camera module  115  and capture non-visible light image data. The ISP  205  can then combine visible light image data and corresponding non-visible light image data to form a hybrid image data that has an acceptable quality. In  FIG. 2 , the ISP  205  can be communicatively coupled to an application processor  210 . The ISP  205  can transmit the hybrid image data, the analyzed visible light image data, the analyzed non-visible light image data, or any combination thereof, for further processing. 
     In  FIG. 2 , the application processor  210  can be a separate processor from the ISP  205 , a main processor of the mobile device  100 , or any processor which can be configured to receive image data from the ISP  205 . The application processor  210  can be directly or indirectly coupled to the mobile device  100 . The application processor  210  can be a processor assembly including one or more processors. The application processor  210  can be a solid state processor, a core processor, or any other processor configured to execute instructions for displaying image data on the mobile device  100 . The application processor  210  can receive image data from the ISP  205 , for example, hybrid image data. The application processor  210  can then process the hybrid image data and execute instructions to display the hybrid image data on a display  220  of the device  100 . 
     The display  220  can be a touchscreen display, a liquid crystal display (LCD), a light emitting diode display (LED), an active matrix organic light emitting diode display (AMOLED), or any other display configured to display graphical information. 
     Also illustrated in  FIG. 2 , the mobile device  100  can include a memory device  215 . For example, the memory device  215  can be transitory memory, non-transitory memory, or any combination thereof. For example, non-transitory memory can be implemented as Random Access Memory (RAM), Read-Only Memory (ROM), flash, ferromagnetic, phase-change memory, and other non-transitory memory technologies capable of storing image data including hybrid image data. Transitory memory can store signals and radio wave data. The memory device  215  can at least store images captured by the visible light camera module  110 , images captured by the non-visible light camera module  115 , and hybrid image data formed by the ISP  205 . In at least one implementation, the memory device  215  can store the instructions for performing the method of adjusting camera image data, as will be described in further detail below in relation to  FIGS. 3-8B . 
       FIG. 3  illustrates a block diagram of the visible light camera module  110 , the non-visible light camera module  115 , the ISP  205 , and memory device  215 , and the application processor  210 . In  FIG. 3 , the visible light module  110  and the non-visible light camera module  115  can be communicatively coupled to the ISP  205 . The ISP  205  can be communicatively coupled to the memory device  215 . As illustrated in  FIG. 3 , the memory device  215  can be external to the ISP  205  and the memory device  215  can be within the mobile device  100  (shown in  FIG. 2 ). In another implementation, the memory device  215  can be integrated with the ISP  205  such that memory device  215  is internal to the ISP. The memory device  215  can be partitioned into at least a first portion  305  and a second portion  310 . The first portion  305  of the memory device  215  can be reserved for storing image data captured by the visible light camera module  110 . The second portion  310  of the memory device  215  can be reserved for storing image data captured by the non-visible light module  115 . 
     While the illustrated embodiment shows the memory device  215  being partitioned into two portions, other organizations and structures of the data are considered within the scope of this disclosure. Another memory arrangement can include a “time based packet alignment” structure. The time based packet alignment arrangement can accept all data packets into the memory (as they become available), without re-shuffling, re-arranging or manipulating the data packets. The data packets are stored sequentially in consecutive memory locations such that the address locations can be continuously incremented. In the time based packet alignment arrangement, the storage of the data packets can ignore the packet type when storing the data packet. For example, the non-visible light data packet can be stored between two visible light data packets. The time based packet alignment arrangement can produce little overhead while accepting incoming information. In at least one implementation of the time based packet alignment, a unique “Packet ID” can be assigned to each packet. In another example, assigning a unique “Packet ID” to each packet can be the only additional action when storing a data packet or data packets to the memory. The Packet ID can be represented by an eight-bit (8-bit) number, such as 10011011. In another example, the Packet ID can be represented by a sixteen-bit (16-bit) number. Other data units can be used to represent the Packet ID as well. Once the Packet ID is assigned, a flag comprising the relevant information associated with the frame or image can be included. The flag can include relevant information, for example one or more of the following: a packet type, an identification number, a time stamp, whether the data (e.g., the frame or image) has been used for image enhancement or not (e.g., for image correction or augmentation), and other system level details. Additionally, as the amount of available memory decreases in response to storing new data packets therein, older data packets can be erased, making room for the newer ones. Such memory management can be controlled by the application processor  210 . 
     In  FIG. 3 , the application processor  210  can be communicatively coupled to the memory device  215  to receive: image data associated with the visible light camera module  110  and stored in the first portion  305  of the memory device  205 , image data associated with the non-visible light camera module  115  and stored in the second portion  310  of the memory device  205 , or hybrid image data formed from the image data associated with the visible light camera module  110  and the image data associated with the non-visible light camera module  115 . 
       FIGS. 4 and 5  illustrate image data stored in the memory device  215 . In  FIG. 4 , the image data is received by the memory device  215  from the ISP  205 . Additionally,  FIG. 4  illustrates image data  410  captured from the visible light camera module  110  (shown in  FIG. 2 ), where no image data is received from the non-visible light camera module  115  (shown in  FIG. 2 ). In  FIG. 4 , the memory device  215  is partitioned into three portions. In other embodiments, the memory device  215  is not partitioned as illustrated. Similar to  FIG. 3 , the first portion  305  can be dedicated to store the image data captured by the visible light camera module  110  (not shown). The second portion  310  can be dedicated to store the image data captured by the non-visible light camera module  115  (not shown). As illustrated in  FIG. 4 , the first portion  305  and the second portion  310  can be partitioned such that the partitions  415  of the first portion  305  correspond to the partitions  420  of the second portion  310 . For example, as illustrated in  FIG. 4 , the partitions  415  of the first portion  305  can be parallel to the partitions  420  of the second portion  310 . In other embodiments, the second portion  310  can be structured such that it only has partitions or members in accordance with a desired ratio of the first portion  305  as will be described below. For example, there can be one partition of the second portion  310  to every four partitions of the first portion  305 . The third portion  405  can be dedicated to store hybrid image data formed from the visible light camera image data and the non-visible light camera image data. In  FIG. 4 , visible light camera image data  410  captured by the visible light camera module  110  can be stored in the first portion  305  of the memory device  215 . 
     In  FIG. 4 , visible light camera image data  410  is stored in the first three partitions  415  of the first portion  305 . For example, as image data captured by the visible light camera module  110  can be stored in the first portion  305  of the memory device  215 , each visible light camera image datum  410  can be stored in a respective partition  415  of the first portion  305 . In at least one implementation, the visible light camera image data  410  can be stored in the first portion  305  of the memory device  215  in the order that the visible light camera image data  410  are captured. Each visible light camera image datum  410  can be time-stamped indicating the time of capture and can be stored in the first portion  305 , thereby providing a reference or marker by which a non-visible light camera image data, captured at a substantially same time as a visible light camera image data  410 , can be retrieved and compared with the captured visible light camera image data  410 . In other embodiments, each visible light camera image data  410  can be marked or otherwise signified with an indicator that can correlate the visible light camera image data  410  with a non-visible light camera image data received at substantially the same time as the visible light camera image data  410 . Additionally, as indicated above, when the visible light camera module  110  and non-visible light camera module  115  cannot record the images at substantially the same time, an interpolation routine or an extrapolation routine can be implemented. 
       FIG. 5  illustrates the memory device  215  illustrated in  FIG. 4 , except that the memory device  215  has stored both visible light camera image data  505  and non-visible light camera image data  510  that have been received and processed by the ISP  205 . As illustrated in  FIG. 5 , twenty visible light camera image data  505  are stored in the first portion  205  of the memory device  215 . Six non-visible light camera image data  510  are in the second portion  310  of the memory device  215 . In  FIG. 5 , the visible light camera image data  505  are allocated in the first portion  305  of the memory device  215  in the order in which the visible light camera image data  505  are received. For example, the first portion  305  is partitioned into a plurality of first partitions  513  (such as visible light partitions). Each visible light camera image data  505  can be stored in a respective first partition  513  of the first portion  305 . Similarly, the non-visible light camera image data  510  are stored in the second portion  310  of the memory device  215  in the order in which the non-visible light camera image data  510  are received. The second portion  310  can also be partitioned into a plurality of second partitions  515  (such as non-visible light partitions). Each non-visible light camera image data  510  can be stored in a respective second partition  515  of the second portion  310 . 
     As illustrated in  FIG. 5 , the first partitions  513  and the second partitions  515  can be parallel to one another, such that visible light camera image data  505  stored in a first partition  513  and non-visible light camera image data  510  stored in an adjacent second partition  515  indicate that the visible light camera image data  505  and the non-visible light camera image data  515  were captured at substantially the same time. For example, in  FIG. 5 , one non-visible light camera image data  510  is captured for every fourth visible light camera image data  505 . Accordingly, a second partition  515  adjacent to every fourth first partition  513  (beginning from the first of the first partitions  513 ) has non-visible light camera image data  510  corresponding to a visible light camera image data  505 . In other implementations, the ratio of visible light camera image data  505  to the non-visible light camera image data  510  can be other than capturing one non-visible light camera image data  510  for every fourth captured visible light camera image data  505 . For example, the ratio can include capturing one non-visible light camera image data  510  for every other or every alternate visible light camera image data  505 , for every fifth visible light camera image data  505 , for every tenth visible light camera image data  505 , for every seventh visible light camera image data  505 , for every twentieth visible light camera image data  505 , for every twenty-fifth visible light camera image data  505 , for every fiftieth visible light camera image data  505 , for every one-hundredth visible light camera image data  505 , for every visible light camera image data, or any other ratio. Increasing the frequency of non-visible light camera image data  510  can increase the accuracy and quality of augmenting the corresponding visible light camera image data  510 ; however, the increased frequency of capturing non-visible light camera image date  510  can require more processing time, more processing power, and more battery power. Alternatively, decreasing the frequency of capturing non-visible light camera images data  510  can decrease the processing time, reduce processing power, and preserve battery power, but the accuracy of augmenting the visible light camera image data  505  may not be as high as if the non-visible light camera image data  510  were captured more frequently. Thus, the frequency of capturing non-visible light camera image data  510  is proportional to the amount of processing power and processing time required to form a higher quality hybrid image. 
     The ratio of the non-visible light image data  510  can be adjusted relative to the visible light image data  505  based on the quality of a hybrid image. For example, if the quality of the hybrid image is below a predetermined threshold, then the number of images acquired by the non-visible light camera module  115  can be increased. Furthermore, while the illustrated example of  FIG. 5  shows some partitions of the non-visible light portion  310  as being empty, the non-visible light partition  515  can be full and a correspondence formula, matrix or other look up feature can be implemented such that values corresponding with the visible light image data  505  can be determined or derived, for example, timestamps. 
     Also illustrated in  FIG. 5 , the memory device  215  can include a third portion  405  for storing hybrid image data formed from a corresponding visible light camera image data  505  and a non-visible light camera image data  510 . For example, in  FIG. 5 , there are four hybrid image data  520  stored in the third portion  405  of the memory device  215 . Details as to the formation of the hybrid image data  520  will now be described with respect to  FIGS. 6A-9 . While  FIGS. 6A-9  illustrate various images, the images illustrated therein are generally not displayed on the display  220  of the mobile device  100 . Rather the illustrations of  FIGS. 6A-9  are provided to illustrate the implementation of the method as presented herein. 
     In an example implementation of the system and method for adjusting image data captured by a mobile device, a visible light camera image  600  (shown in  FIG. 6A ) can be captured by a visible light camera module  110  of a mobile device  100 . In  FIG. 6A , the visible light camera image  600  captures a scene of a house  605 , a car  615 , a person  610  walking towards the house  605 , and a shadow  620  of the house  605  and the car  615 . However, as illustrated in  FIG. 6A , the region of the image containing the person  610  in the image  600  is out of focus (as represented by hashed lines). That is, a quality of the image  600  is below a predetermined threshold. For example, the image  600  can be of an unacceptable quality based on a determination that an image sharpness, an exposure time (for example, based upon a determination of a level of misalignment for lens exposure time), a luminance, a presence of dead pixels (for example, underexposed, overexposed, or unexposed pixels), missing portions of an image, a blurriness, or any other predetermined characteristic of an image falls below a predetermined threshold. In other embodiments, more than one characteristic can be analyzed, and a determination made if the more than one characteristic is below the respective thresholds. When more than one characteristic is analyzed, the determination of whether an image needs augmentation can be based on the determination that one of the more than one characteristic is below the respective predetermined threshold. Thus, if a single characteristic is below the respective predetermined threshold, the image can be augmented. In other embodiments, a determination can be made that a number of characteristics are below respective predetermined threshold, but the determination that the image will not be augmented can be made if a single characteristic if a selected number of characteristics are above the respective threshold, for example if the characteristics of overexposure and underexposure are above the respective thresholds then no augmentation can be performed. 
     The predetermined threshold can represent the minimum values of predetermined characteristics of an image that correspond to the minimum quality of an acceptable image. In response to or substantially simultaneously with the capture of the visible light camera image  600 , a request can be transmitted to a non-visible light camera module  110  to capture a non-visible light camera image. From the non-visible light camera image, the ISP  205  can fix, correct, or augment the unacceptable visible light image  600  with at least a portion of the non-visible light image, such that a hybrid image having a sufficient quality can be formed. 
     In  FIG. 6B , a non-visible light camera image  650  is illustrated which has been captured in response to the determination that the visible light image  600  has a quality factor that is unacceptable. That is, in response to a determination that a quality factor of the visible light image  600  falls below a threshold, a request to capture a non-visible light image can be transmitted to the non-visible light camera module  115 . The non-visible light camera module  115 , consequently, can be powered on or activated to an active state and can capture a non-visible light image  115 . As illustrated in  FIG. 6B , the house  655  and the person  660  of the non-visible light image  650  are clearer than the corresponding house  605  and person  610  of the visible light image  600 . Additionally, as illustrated in  FIG. 6B , the non-visible light image  650  does not include the shadows  620  as found in  FIG. 6A . 
     Furthermore, comparing  FIG. 6B  to  FIG. 6A , the non-visible light image  650  can be shifted or captured from a different vantage point or perspective than the visible light camera image  600 . The shifted image of the non-visible light image  650  can be due to the non-visible light camera module  115  being mounted some distance away from the visible light camera module  110 . In other instances, there is little to no shift in the images from the visible light image  600  as compared to the non-visible light image  650 . In  FIG. 6B , the shifting of the non-visible light image  650  as compared with the visible light camera image  600  has been exaggerated for illustrative purposes. 
     As illustrated in  FIG. 6B , the house  655  in the non-visible light image  650 , the car  615 , and the person  660  appear shifted as compared to same objects in the visible light image  600 . The shift can be due to the different perspectives of the non-visible light camera module  115  and the visible light camera module  110  resulting from the orientation of the non-visible light camera module  115  with respect to the visible light camera module  110 . For example, the non-visible light camera  115  and the visible light camera  110  can be disposed side-by-side, at an angle to one another, or one on top of the other. In at least one implementation, the configuration of the hardware components of visible light camera module  110  and non-visible light camera module  115  can result in the respective images appearing shifted compared to one another. For example the visible light camera module  110  and the non-visible light camera module  115  can be configured to have different resolutions that result in the respective images appearing shifted compared to one another. In another implementation, the non-visible light camera  115  and the visible light camera  110  can be oriented one on top of the other, and a mirror or prism can be positioned therebetween such that the images captured from the visible light camera  110  and the non-visible light camera  115  have substantially similar perspectives. In such an implementation, the non-visible light image may not appear to be shifted when compared to the visible light camera image. To account for the variance in perspective, resolution, and zooming level between the non-visible light camera  115  and the visible light camera  110 , calculations and image analysis can be performed to determine which portions of the visible light image  600  correspond with which portions of the non-visible light image  650 . 
     For example,  FIGS. 7A and 7B  illustrate the implementation of the ISP  205  in determining which portion of the visible light image  600  is to be augmented, corrected, or fixed and determining which portion of the non-visible light image  650  corresponds to that of the visible light image  600 . Specifically, in  FIGS. 7A and 7B , the contours  700  of the house  605  in the visible light image  600  and the contours  750  of the house  655  in the non-visible light image  650  are identified. As illustrated in  FIGS. 7A and 7B , the contours  700 ,  750  of the houses  605 ,  655  are represented by bolded outlines. 
     The contours  700 ,  750  of the house  605 ,  655  are illustrative of selecting a major contour for the images. In other embodiments, the contour could have been selected to be the road or other structure or significant shape. In at least one embodiment, a plurality of contours can be determined. 
     With the contours  700 ,  750  identified, the contours  700 ,  750  can be used as references for determining which portions of the visible light image  600  correspond to which portions of the non-visible light image  650 , as illustrated in  FIGS. 8A and 8B . 
       FIGS. 8A and 8B  illustrate the process of the ISP  205  identifying the portion of the visible light image  600  that includes a region  800  or portion having a quality factor that is less than a predetermined threshold.  FIG. 8A  illustrates the visible light image  600  in which the contour  700  of the house  605  has been identified (shown as a bolded outline of the house  605 ). Two points  815 ,  820  on the contour  700  are used to triangulate pixel data within the region  800  of the visible image  605  that has a quality factor that is less than a predetermined threshold. For example, a first vector  805  can be drawn from the first point  815  of the contour  700  to the region  800 . A second vector  810  can be drawn from a second point  820  of the contour  700  to the region  800 . The magnitude and direction of the first vector  805  and the second vector  810  can then be used to determine a corresponding region or corresponding portion of the non-visible light image  650  (shown in  FIG. 8B ). 
     Using the contour  700  of the visible light image  600  and the contour  750  of the non-visible light image  650 , a scaling factor can be determined. The scaling factor can be determined in at least two dimensions. When the image is a three dimensional image, an additional scaling factor can be determined. 
     As illustrated in  FIG. 8B , a third vector  855  can be drawn from a third point  865  on the contour  750  of the house  655  of the non-visible light image  650  to a region  850  of the non-visible light image  650  that corresponds to the region  800  of the visible light image  600 . Similarly, a fourth vector  860  can be drawn from a fourth point  870  of the contour  750  of the house  655  of the non-visible light image  650  to the region  850  of the non-visible light image  650 . The third vector  855  and fourth vector  860  are calculated using the appropriate scaling factors along with the first vector  805  and second vector  810 , respectively. Thus, the region of the non-visible light image  600  corresponding to the region of the visible light image  650  having a quality factor below a predetermined threshold can be determined. 
     With the corresponding regions  800 ,  850  of the visible light image  600  and the non-visible light image  650  identified, the region  850  of the non-visible light image  650  can be combined with the visible light image  600  to form a hybrid image  900 , as illustrated in  FIG. 9 . For example, the region  850  of the non-visible light image  650  can replace the region  800  of the visible light image  600 . In other implementations, the hybrid image  900  can be formed on a pixel by pixel basis. For example, the pixels of the region  850  of the non-visible light image  650  can replace the pixels of the region  800  of the visible light image  600  to result in a hybrid image  900 , such as illustrated in  FIG. 9 . 
     In another implementation, the pixels, of the region  800  of the visible light image  600 , that are determined to have a quality factor below the predetermined image can be replaced by pixels of the corresponding region  850  of the non-visible light image  650 . For example, the pixels of the visible light image  600  can be augmented with data from the pixels of the non-visible light image  650  to enhance one or more characteristics of the visible light image  600 , such that the color of the visible light image  600  is maintained. In at least one embodiment, the visible light image  600  (for example, the visible light image frame or the raw data frame of the visible light image  600 ), and the pixels thereof can form the foundation of the augmented or hybrid image  900  that will be displayed to the user. Each individual component of the visible light image  600  can be replaced by the “hybrid replica” or “augmented section” derived from augmenting or combining similar sections of the non-visible light image  650  and the visible light image  600 . When augmenting the visible light image  600 , the enhancements of the visible light image  650  are based on the non-visible light camera data  650  modifying the visible light image  600  such that the scaling and pixel density of the visible light image  600  is conserved, but the portion  800  or portions having a quality factor below a predetermined threshold are augmented. In other embodiments, the augmentation of the visible light image data  600  can be across all pixels of the visible light camera data  600 . 
     In one example, the technique used to augment at least a portion of the visible light image  600  or form a hybrid replica of at least a portion of the visible light image  600  can be “sub pixel rendering.” Sub pixel rendering takes advantage of the fact that each individual pixel consists of individual RED, GREEN and BLUE components. When the color of the pixel is determined to be below the threshold, the color ratio of the original pixel is augmented based on the data from the non-visible light image  650  to produce a hybrid image  900  (shown in  FIG. 9 ). In another implementation, the size, resolution, and zoom level of the non-visible light image  650  can be adjusted to correlate with the size, resolution, and zoom level of the visible light image  600 . The entire non-visible light image  650  can then be combined with the entire visible light image  600 , and the pixels of the visible light image  600  which have a quality factor that falls below a threshold value can be replaced with the pixels of the non-visible light image  650  to result in a hybrid image  900 , as illustrated in  FIG. 9 . 
       FIG. 9  illustrates a hybrid image  900  formed from the visible light image  600  of  FIGS. 6A ,  7 A, and  8 A and the non-visible light image  650  of  FIGS. 6B ,  7 B, and  8 B. As illustrated in  FIG. 9 , the shadows  620  of the house  605  and car  615  are provided. Also provided is the person  660  of the non-visible light image  650 . That is, the missing portion or low quality portion  800  (shown in  FIG. 8A ) of the visible light image  600  is replaced with the corresponding portion  850  (shown in  FIG. 8B ) of the non-visible light image  650 , thereby correcting, fixing, or augmenting the visible light image  600  to result in the hybrid image  900 . Accordingly, the resulting hybrid image  900  can have a quality factor that at least matches or exceeds the threshold for an acceptable image. 
       FIG. 10  is a flow chart of a method of adjusting camera image data received by a mobile device. The method  1000  illustrated in  FIG. 10  is provided by way of example, as there are a variety of ways to carry out the method. Additionally, while the example method  1000  is illustrated with a particular order of steps, those of ordinary skill in the art will appreciate that  FIG. 10  and the steps illustrated therein can be executed in any order that accomplishes the technical advantages of the present disclosure and can include fewer or more steps than illustrated. 
     Each block shown in  FIG. 10  represents one or more processes, methods or subroutines, carried out in example method  1000 . The steps illustrated in  FIG. 10  can be implemented in a system including a mobile device  100  such as a smartphone, an electronic tablet, or any other mobile device capable of at least accepting data, transmitting data, and executing commands. Each block shown in  FIG. 10  can be carried out by the ISP  205  (which can be one or more processors and/or one or more processing systems) of the mobile device  100  illustrated in  FIG. 2  or the application processor  210  (which can be one or more processors or one or more processing systems). The flow chart illustrated in  FIG. 10  will be described in relation to and make reference to the mobile device  100  in  FIG. 2 , the memory device illustrated in  FIG. 5 , and the images illustrated in  FIGS. 6A-9 . 
     The method  1000  can begin at block  1005 . At block  1005 , the camera of the mobile device  100  can be invoked. For example, the camera (such as, the visible light camera module  110 , the non-visible light camera module  115 , or both) can be invoked by initiating a camera application. The camera application can allow for capturing still photos or images or a series of pictures, such as videos. In other implementations, the camera can be invoked by a selection of a shortcut key assigned to initiating the camera of the mobile device  100 . After the camera is invoked, the method  1000  can proceed to block  1010 . 
     At block  1010 , a determination can be made if an augmented mode is active. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as a main mobile device processor (not shown), can make the determination. If the augmented mode is not active, the method can proceed to block  1015 . In at least one embodiment, the augmented mode can always be active such that the determination block  1010  can be skipped. 
     At block  1015 , the camera of the mobile device  100  can be operated without augmentation. However, if the augmented mode is active, the method can proceed to block  1040 . 
     At block  1040 , a determination can be made as to whether augmentation should be implemented. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor (not shown), can make the determination. This determination can be based on input received by the mobile device from the user, for example, when the user indicates that augmentation should be implemented. Alternatively, augmentation can be implemented unless the user has indicated that augmentation is not desired. The user can indicate that augmentation should be implemented by selecting such an option from a camera setting menu  1305  (shown in  FIG. 13 ). In other embodiments, a notification can be presented on the display requesting the user to select whether augmentation should be implemented when capturing images. If the user has indicated that augmentation should be implemented at a specific ratio, the method can proceed to block  1045 . If a specific ratio has not been indicated, the method  100  can proceed to block  1020 . 
     At block  1045 , a ratio can be determined from a user input received at the mobile device  100 . For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor (not shown), can make the determination. The ratio can indicate the frequency of capturing non-visible light camera image data  650 . For example, the frequency of capturing non-visible light camera image data  650  can include capturing one non-visible light camera image data  650  for every other visible light camera image data  600 , for every fifth visible light camera image data  600 , for every tenth visible light camera image data  505 , for every seventh visible light camera image data  600 , for every twentieth visible light camera image data  600 , for every twenty-fifth visible light camera image data  600 , for every fiftieth visible light camera image data  600 , for every one-hundredth visible light camera image data  600 , for every visible light camera image data, or any other ratio. The non-visible light camera module  115  can remain in the powered-down or low-power state until a non-visible light camera image is captured, since the frequency of non-visible light camera image data capturing is predetermined or preset. When the non-visible light camera module  115  remains in the low-power state or powered-down state until a non-visible light camera image is needed, processing power, processing time, and battery life can be preserved. In other embodiments, the powering of the non-visible light camera module  115  can be as described above. After the ratio is determined, the method can proceed to block  1050  as will be described below. 
     Blocks  1040  and  1045  can correspond to a user-initiated image augmentation mode. However, the augmentation mode can be automatic or can operate under default settings or automatic settings. 
     If augmentation is automatically determined or the user has indicated that automatic augmentation should be implemented, the method  1000  at block  1020  receives image data  600  from a visible light camera module  110  of the mobile device  100 . The visible light data can be in the form of a raw data frame. The visible light data captured by the visible light camera module  110  can be transmitted to the ISP  205  of the mobile device  100 , and the method  1000  can proceed to block  1025 . In at least one implementation, the visible light camera image data  600  can be time-stamped to aid in determining a corresponding a non-visible light camera image data  650  for augmenting the visible light camera image data  600 , as will be described in further detail below. 
     At block  1025 , a quality factor of the image data  600  from the visible light camera module  110  can be determined based at least on at least one predetermined characteristic. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor (not shown), can make the determination. For example, the at least one predetermined characteristic can include a sharpness, an exposure time (for example, based on a determination of a level of misalignment for lens exposure time), total exposure time, luminance, whether a pixel of the image data is dead, or other characteristics of images. The quality factor can be a measurement of a predetermined characteristic of the image  600 . For example, a sharpness level, a lens exposure time (such as a total exposure time), a brightness measurement, a luminance value, a light intensity measurement, a luminance remittance, a luminous existence, a white balance measurement, a black and white level, a sharpness level, a blurriness level, a color level, a contrast level, or any other measurement of a predetermined characteristic of images may be used. The quality factor can be determined on a pixel by pixel basis, for a portion of the image data  600 , or for the entire image data  600 . By determining the quality factor of the image on a pixel by pixel basis or on a portion by portion basis, problematic pixels or portions of the image can be identified (for example, as discussed above in relation to  FIGS. 6A-8B ). The problematic pixels or portions can be indicative of a dead pixel, as described above, or a portion of the image that is a poor image quality. Such identified pixels and portions can then be identified or marked for augmenting as will be described below. After the quality factor of the captured image  600  is determined, the method  1000  can proceed to block  1030 . 
     At block  1030 , a comparison of the quality factor to a predetermined threshold can be made. For example, the comparison can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the comparison. For example, the predetermined threshold can be associated with at least one of the predetermined characteristics. The predetermined threshold can indicate a minimum level or measurement of at least one predetermined characteristic that represents a sufficient or acceptable quality for an image. The minimum level can depend on the predetermined characteristic. Some examples of the minimum level are presented herein, but others can be implemented as well. The minimum level can be user defined. For example, when color uniformity is the quality factor, the minimum level can be a color uniformity of 95% uniformity. In one example, the quality factors can be measured by the ISP. In one example, the ISP can probe selected pixels, groups of pixels, or both selected pixels and groups of pixels in the image data. The ability to perform analysis on the pixel level allows for determination of when the color changes from dark to bright. In another example, when the color changes rapidly, the color change indicates a camera lens exposure time issue, which can be caused from overexposure or underexposure. Thus, when comparing pixel color it can be determined the amount of color change that has occurred at the pixel or group of pixels. The amount of color change can be compared to a predetermined threshold, which in one example is a 10% deviation or a 90% consistency. Additionally, a review of the image histogram can be performed such that the color uniformity is sampled across a plurality of images. In one embodiment, one or more regions are identified for examination and then scanned for uniformity. In one example, the consistency of color should be greater than 98% consistent or have a deviation of less than 2%. At block  1030 , the comparison of the quality factor to the predetermined threshold can be a determination as to whether the quality factor is above the predetermined threshold. If the quality factor is above the predetermined threshold, the method can proceed to block  1035 . 
     At block  1035 , if the quality factor is above the predetermined threshold, the visible camera image data  600  can be used. For example, the visible camera image data  600  can be transmitted from the ISP  205  to the application processor. That the quality factor is above the predetermined threshold can indicate that the image captured by the visible light camera module  110  is of sufficient or acceptable quality to be used by the application processor (for example, for displaying the image on the display  220  of the mobile device  100 ). 
     If, however, the quality factor is not above the threshold, the method can proceed to block  1050 . For example, if the quality factor is below or equal to the threshold, the method can proceed to block  1050 . At block  1050 , a request can be transmitted to obtain image data from a non-visible light camera module  115 . For example, the request can be transmitted by the ISP  205 . The request can be received by the application processor  210  or any other suitable processor coupled to the non-visible camera light module  115 . In response to the request for image data from the non-visible light camera module  115 , the method can proceed to block  1055 . In other embodiments, the request can be transmitted from a first portion of the ISP  205  to execute a second portion of the ISP  205  to obtain or transmit a command to obtain image data from the non-visible light camera module  115 . The non-visible light camera module  115  can be fully powered on in response to the request for non-visible light camera image data. In other implementations, the non-visible light camera module  115  can be powered on while the visible light camera module  110  is powered on. The visible light camera module  110  and the non-visible light camera module  115  can be powered and synchronized with each other such that when one camera module is capturing an image the other camera module is placed in a low-power state or powered off. After the request for image data from the non-visible light camera module  115  is received, the method can proceed to block  1055 . 
     At block  1055 , image data can be received from the non-visible light camera module  115 . In another implementation, the image data from the non-visible light camera module  115  can be retrieved from a memory device  215  which stores image data captured by the non-visible light camera module  115 , as discussed above in relation to  FIG. 5 . The non-visible light camera image data  650  can be time-stamped similarly as the visible light camera image data  600 . The time-stamps of the non-visible light camera image data  650  can serve as an indicator or reference for identifying which non-visible light camera image data  650  corresponds to the visible light camera image data  600 . That is, the time-stamps aid in determining which non-visible light camera image data  650  was captured substantially simultaneously when a visible light camera image data  600  was captured. In other words, the time-stamps can link the visible light camera image data  600  to a corresponding non-visible light camera image data  650  that is likely to have a substantially similar scene as that captured in the visible light camera image data  600 . Receiving image data from the non-visible light camera module  115  can also be received at a predetermined ratio (as described above in relation to  FIG. 5  and as discussed in relation to Block  1045 ) to the visible light camera module  110 . For example, one non-visible light camera image data  650  can be captured or received for every four visible light camera image data captured or received. Other ratios as described above can also be implemented. After the non-visible light camera image data  650  is received, the method can proceed to block  1060 . 
     At block  1060 , the visible light camera image data  600  and the non-visible light camera image data  650  can be combined, augmented, or both combined and augmented. For example, the combination, augmentation, or both the combination and augmentation can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the combination, augmentation, or both the combination and augmentation. For example, as discussed above, the problematic or low quality pixels or portions of the visible light camera image data  600  that are identified at blocks  1025  and  1030  can be combined with corresponding pixels or portions of the non-visible light camera image data  650 . As described above, the visible light camera image data  600  can be combined with the non-visible light camera image data  650  on a pixel-by-pixel basis, a portion-by-portion basis, or can be overlapped such that the dead or low-quality pixels of the visible light camera image data  600  are filled in or replaced with the corresponding pixels of the non-visible light camera image data  650 . 
     In another example, non-visible light image data can be used to improve image quality, using “Histogram Blocks,” of the visible light image. When the visible light camera  110  captures images, the image data can be stored in the memory  215  as described above. Additionally, the present method can analyze image characteristics of the visible light image data over time. For example, the memory  215  can be scanned across time for inconsistencies such as contour blurriness, pixel color flickering, or color non-uniformity. In one embodiment, three scans can be performed substantially in parallel. The three scans can be: 1) a scan for pixel consistency with respect to frame histogram (e.g., where a predetermined threshold can be 95%), 2) a scan for pixel accuracy or quality can be measured with the respect to the other surrounding pixels, and 3) a scan for dynamic range swings over time (e.g., where the threshold is a predetermined number of dynamic range swings from minimum to maximum). After combining the visible light camera image data  600  and the non-visible light camera image data  650 , the method can proceed to block  1065 . 
     At block  1065 , a hybrid image can be produced. For example, the production can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the production. For example, the hybrid image  900  can be formed from the visible light camera image data  600  and the non-visible light camera image data  650 . The hybrid image  900  can be stored in the memory device  215  of the mobile device  200 . In other implementations, the hybrid image  900  can be displayed on a display  220  of the mobile device  100 . 
       FIG. 11  illustrates a flow chart of another implementation of a method  1100  of adjusting camera image data captured by a mobile device  100 . Blocks  1105 - 1135  of  FIG. 11  are substantially similar to blocks  1025 - 1035  and  1050 - 1065 , respectively.  FIG. 11  differs from  FIG. 10  in that  FIG. 11  includes the additional step of determining a quality factor of the hybrid image, at block  1140 . 
     At block  1140 , the ISP  205  can determine the quality factor of the hybrid image  900 . For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the determination. The quality factor can be similar to that as described in  FIG. 10  at block  1030 . After the quality factor of the hybrid image  900  is determined, the quality factor can be compared to a predetermined threshold. For example, the predetermined threshold can be the same as the first threshold as described in relation to  FIG. 10  or can be a different threshold, such as a second predetermined threshold associated with predetermined characteristics of hybrid images. If the quality factor of the hybrid image  900  is above the predetermined threshold, the method  1100  can proceed to block  1145 . In at least one embodiment, the predetermined threshold level can be user defined, both as a part of the initial configuration and dynamically as images are acquired. The user inputted threshold can be written to an ISP register (not shown) such that the ISP register contains the current threshold. In one example, when the threshold of the hybrid image is the same as the threshold of the visible light image, the resultant hybrid image must be of a sufficient quality to have passed the initial analysis of the quality factor. In other instances, it is desirable to change the threshold of the quality factor to be different from the visible light image. For example, the threshold can be lowered since the resultant image is a hybrid image to account for the fact that certain losses of image data can occur during the composition of the hybrid image. In other embodiments, since a hybrid image is composed of the visible light image data and the non-visible light image data, the hybrid image can be held to a higher threshold such that the hybrid image must satisfy more difficult requirements. 
     In another embodiment, if a maximum picture quality is required, the ISP can periodically change the predetermined threshold levels, provided that the previous predetermined threshold was satisfied. Additionally, in at least one embodiment, after each increase of the predetermined threshold levels, a testing period can be implemented to determine if the new threshold can be met. If the increased value of the predetermined threshold is met, then the increased value becomes the predetermined threshold. In at least one embodiment the testing period can be optional. For example if there is a need to preserve battery life, having an optional testing period can reduce processing power consumption thereby increasing battery life. 
     In still another embodiment, a default criteria level or threshold level can be locked-in or unchanged until the user edits the threshold. Such default criteria level can act as an absolute minimum for image quality. If the default criteria level setting further includes a default-selected setting that allows the ISP to independently increase all criteria levels, eventually over time, the ratio between visible light image frames versus hybrid frames can become off-balance, and result in all the images being hybrid images. In such a situation, excessive raw frame or raw image data computation resource requirements can deplete battery life, can cause additional heat dissipation, and can decrease the system&#39;s ability to sustain operation. 
     At block  1145 , the hybrid image  900  can be used. For example, the hybrid image  900  can be transmitted to the application processor  210  of the mobile device  100 . In one implementation, the hybrid image  900  can be transmitted to the application processor  210  and the application processor  210  can execute instructions to display the hybrid image  900  on the display  220  of the mobile device  100 . If, however, the quality factor of the hybrid image  900  is not above the predetermined threshold (for example, is below or is less than or equal to the predetermined threshold), the method can proceed to block  1150 . 
     At block  1150 , the ratio of capturing non-visible light camera image data as compared to visible light camera image data (for example, the frequency of capturing non-visible light camera image data) can be changed to a different ratio. For example, the changing of the ratio can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can change the ratio. For example, if the quality factor of the hybrid image  900  indicates that the hybrid image is of a poor quality, the ratio of received image data from the non-visible light camera  115  to the visible light camera  110  can be increased. After the ratio is increased, the method can return to block  1125 , which corresponds to block  1055  of  FIG. 10 . In  FIG. 11 , the method  1100  can cycle through blocks  1125 - 1150  until the quality factor of the hybrid image  900  satisfies, is above, or is greater than or equal to the predetermined threshold associated with the characteristics of hybrid images. 
     In another implementation, in response to determining that the quality factor for the hybrid image  900  falls below the predetermined threshold, the image sensor associated with the visible light camera module  110  can be adjusted. For example, a brightness level, a luminance level, a contrast level, an exposure time, a sharpness level, or any other characteristic of the image can be adjusted. That is the image sensor associated with the visible light camera module  110  can be adjusted to account for the poor quality factor of the previously-captured image. 
       FIG. 12  illustrates a flow chart of another implementation of a method of adjusting camera image data. Specifically,  FIG. 12  illustrates a flow chart of blocks for producing hybrid image data. The blocks illustrated in  FIG. 12  can be included in the methods  1000 ,  1100  of  FIGS. 10 and 11 , or can include at least one of the steps therein. In other implementations, the method steps illustrated in  FIG. 12  can be included in a method different from those illustrated in  FIGS. 10 and 11 . For example, the method  1200  of producing the hybrid image illustrated in  FIG. 12  can follow block  1055  of  FIG. 10  or block  1125  of  FIG. 11 . 
     In the specific implementation illustrated in  FIG. 12 , the method  1200  of producing the hybrid image can be included in block  1060  of  FIG. 10  or block  1130  of  FIG. 11 . That is, combining image data from the visible and non-visible light camera modules, as illustrated in blocks  1060  and  1130  of  FIGS. 10 and 11 , respectively, can include the steps illustrated in  FIG. 12 . For example, combining and/or augmenting image data from the visible light and non-visible light camera modules can include block  1205  of  FIG. 12 . For example, the combination and/or augmentation can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the combination, augmentation, or both the combination and the augmentation. 
     At block  1205 , a determination of at least one contour of visible light camera image data  600  can be made. For example, determining at least one contour of the visible light camera image data can be performed by the ISP  205  of the mobile device  100 . Determining at least one contour of the visible light camera image data  600  can include determining a contour  700  or an outline of an object captured by the visible light camera  110 . After determining at least one contour of the visible light camera image data  600 , the method can proceed to block  1210 . 
     At block  1210 , a determination of the characteristics of the contour  700  can be made. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the determination. The determination of the characteristics of the contour can be such that at least two scaling factors are generated for the visible light image data. The scaling factors provide for a determination of the location of a portion of the image data from the contour  700 . After the characteristics of the contour  700  have been determined the method can proceed to block  1215 . 
     At block  1215 , a determination of the location of data that do not meet a predetermined threshold can be made. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the determination. The predetermined threshold can be any predetermined threshold associated with an acceptable quality of an image, as described above. For example, the predetermined threshold can be a minimum level of image sharpness, a minimal level of misalignment for less exposure time, a minimum level of luminous existence, a minimum contrast level, or any other predetermined threshold associated with characteristics of pixels of an image having an acceptable quality. The location of the pixel data that do not meet the predetermined threshold can be determined based at least in part on measurements from the at least one contour of the image data from the visible light camera module  110 . For example, the location of the visible pixels that do not meet the predetermined threshold can be determined by triangulating the location of the visible pixels from points on the contour  700 . That is, a first vector  805  can be drawn from a first point  815  on the contour  700  to the pixel(s) that do not meet the predetermined threshold, as illustrated in  FIG. 8A . A second vector  810  can be drawn from a second point  820  on the contour  700  to the pixel(s) that do not meet the predetermined threshold. Based on the first vector  805  and the second vector  810 , the location of the pixel(s) that do not meet the predetermined threshold can be approximated. The magnitude and direction of the first vector  805  and the second vector  810  can be determined and used to determine a location in the non-visible light camera image  650  that corresponds to the visible light pixel(s) that do not meet the predetermined threshold, as will be discussed below. After the determination of the location of the pixel data, the method can proceed to block  1230 . 
     At block  1230 , a determination of at least one contour of the non-visible light camera image data can be made. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the determination. In another implementation, the determination can be made in parallel, substantially simultaneously, or concurrently with the determination of the contour of the visible light camera image data at block  1205 . Specifically, at block  1230 , determining at least one contour of the non-visible light camera image data  650  can include determining a contour  750  or an outline of an object captured by the non-visible light camera  115 . After determining at least one contour of the non-visible light camera image data  650 , the method can proceed to block  1235 . 
     At block  1235 , a determination of the characteristics of the contour  650  of the non-visible light camera image data  650 . For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the determination. The determination of the characteristics of the contour  650  can be such that at least two scaling factors are generated for the non-visible light image data. The scaling factors along with the scaling factors and vectors of the visible light image data provide for a determination of the location of a portion of the non-visible image data corresponding to the portion of the visible light image data that is below the predetermined quality factor. After the characteristics of the contour  750  have been determined the method can proceed to block  1240 . 
     At block  1240 , the location of non-visible light pixels (for example, corresponding pixels or corresponding non-visible light pixels) that correspond to the visible pixels that do not meet the predetermined threshold can be determined. For example, the determination can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the determination. For example, a corresponding portion the non-visible light image  650  associated with the non-visible light pixels that correspond to the visible pixels that do not meet the predetermined threshold can be located based on a comparison of the at least one contour of the image data from the visible light camera module and the at least one contour of the image data from the non-visible light camera module. In at least one implementation, the first vector  805  and the second vector  810  can be used to find the location of the non-visible light pixels that correspond to the visible light pixels that do not meet the predetermined threshold. For example, the magnitude and direction of the first vector  805  and the second vector  810  associated with the visible light camera image data  600  can be used to draw substantially similar vectors (for example, a third vector  855  and a fourth vector  860 ) using the scaling factors from the contour of the non-visible light camera image  650 . Based on the direction and the magnitude of the first vector  805  and the second vector  810  associated with the visible light camera image  600 , a third vector  855  and a fourth vector  860  of corresponding direction and magnitude (for example based on a ratio of the resolution of the non-visible light camera image  650  to the resolution of the visible light camera image  600 ) can be determined. The corresponding non-visible light image pixels can then be triangulated from a third point  865  and a fourth point  870  on the contour  750  of the non-visible light camera image  650  that correspond to first point  815  and the second point  820  of the contour  800  of the visible camera image  600  using the third vector  850  and the fourth vector  860  of the non-visible light camera image  650 , as illustrated in  FIG. 8B . After the location of the corresponding non-visible light pixels is determined, the method can proceed to block  1220 . 
     At block  1220 , the pixel data from the visible light camera image data can be updated with the pixel data from the non-visible light camera image data. For example, the updating can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the updating. Updating the pixel data of the visible light camera image data  600  with the non-visible light camera image data  650  can include replacing the pixel data of the visible light camera image data  600  that do not meet the predetermined threshold with the corresponding pixel data from the non-visible light camera image data  650 . In another implementation, updating the pixel data of the visible light camera image data  600  can include replacing a portion of the visible light camera image data  600  associated with the pixels that do not meet the predetermined threshold with a corresponding portion of the non-visible light camera image data  650  that include the non-visible light pixels that correspond to the visible light pixels that do not meet the predetermined threshold. The pixel content manipulation of augmentation can include changing an intensity of red, green and blue values based on the ISP&#39;s assessment of image quality, as described above. After the pixel data from the visible light camera image data  600  is updated, the method can proceed to block  1225 . 
     At block  1225 , hybrid image data can be produced. For example, the production can be made by one or both of the ISP  205  and the application processor  210 . In another embodiment, a different processor, such as the main mobile device processor, can make the production. The hybrid image data  900  can be produced by recording or storing the visible light camera image data updated in a hybrid portion  405  of the memory device  215 . In another implementation, producing hybrid image data  900  can include creating a new image file comprising the visible light camera image data  600  updated with the corresponding pixels of the non-visible light camera image data  650  and saving the new image file in the memory device  215 . 
     While  FIG. 12  is described as determining the contours of the non-visible light camera image data  650  and the visible light camera image data  600 , in another implementation, at least one contour of a previous hybrid image can be determined. A determination that at least one portion of the image data from the visible camera module  110  is outside of an acceptable threshold for image quality can be made. The location of the at least one portion of the image data from the visible light camera image data  600  that is outside the acceptable threshold can be determined based on measurements from at least one contour of the image data from the visible light camera module, for example by triangulating the location of the portion based on vectors drawn from the at least one contour. A portion of the image data from the non-visible light camera module  115  and the image data from the previous hybrid image that corresponds to the portion of the image data from the visible light camera image data  600  can be determined, for example by drawing vectors of substantially similar magnitude and direction as those determined for the visible light camera image data  600  from contours of objects in the non-visible light image data  650  and the previous hybrid image data. The visible light image camera image data  600  can be updated with the image data from at least one of the non-visible light camera module  115  or the previous hybrid image at the corresponding portion. In another implementation, a portion of the visible light image camera image data  600  can be updated with a corresponding portion of the non-visible light camera image data  650  or the previous hybrid image at the corresponding portion, or a combination thereof. 
     In any one of the methods illustrated in  FIGS. 10-12 , the augmentation (such as the combination of the non-visible light camera image data and the visible light camera image data or the updating of the visible light camera image data) can be a looping process. For example, the augmentation can continue looping until the visible light camera image data has a quality factor that satisfies, exceeds, or is greater than the predetermined threshold. 
     While the methods presented above can be described as a camera augmentation mode or an assistive mode that is automatic, the augmentation mode can be user-enabled. For example, by making selections on a device as illustrated in  FIG. 13 .  FIG. 13  illustrates a front  150  of a mobile device  100 . The display  220  of the mobile device  105  can display user interface  1300 . In  FIG. 13 , user interface  1300  can be associated with a camera application and can include a camera menu  1305 . The camera menu  1305  can include a plurality of settings which can be designated or selected to enable an augmentation mode, such as those described above. Specifically, the camera menu  1305  can include a setting for automatic augmentation  1310 , a setting for no augmentation  1315 , and a setting for user-defined augmentation  1320 . 
     In  FIG. 13 , the setting for automatic augmentation  1315  is selected. As the setting for the automatic augmentation  1315  is selected, the ISP  205  can be set to a mode to automatically determine whether each visible light camera image data is outside of predetermined thresholds associated with characteristics of images having acceptable quality factors and can automatically augment the visible light camera image data with non-visible light camera image data. In such a mode, the frequency that the non-visible light camera image data is received can be dynamically adjusted based on the determined quality factor of the received visible light camera image data. That is, if the received visible light camera image data falls below a predetermined threshold associated with quality factors by a small amount, the frequency of capturing non-visible light camera image data can be less frequent. Alternatively, if the received visible light camera image data falls below the predetermined threshold by a large amount, the frequency of capturing non-visible light camera image data can be more frequent. 
     If the setting for no augmentation  1315  is selected, no augmentation will be applied to the visible light camera image data. That is, the visible light camera image data  600  will not be augmented by the ISP  205  and will be transmitted to the application processor  210  for display on the display  220  of the mobile device  100 . 
     If the setting for a user-defined augmentation  1320  is selected, augmentation will applied to the visible light camera image data based on the user-defined settings associated with augmentation  1325 . For example, as illustrated in  FIG. 13 , the user-defined settings associated with augmentation  1325  can include selecting a frequency of capturing or receiving non-visible light camera image data  650 . The frequency of capturing receiving non-visible light camera image data  650  can be represented as a ratio, as illustrated in  FIG. 13 . The ratio can indicate a number of non-visible light camera image data  650  captured in comparison to a number of visible light camera image data  600  captured. For example, in  FIG. 13 , the ratios can include: 1:100 (one non-visible light camera image data captured for every 100 visible light camera image data), 1:75 (one non-visible light camera image data captured for every 75 visible light camera image data), 1:50 (one non-visible light camera image data captured for every 50 visible light camera image data), 1:30 (one non-visible light camera image data captured for every 30 visible light camera image data), or any other ratio. In other implementations, the user-defined settings can include a maximum and a minimum number of visible light images captured for every non-visible light camera image. 
     Examples within the scope of the present disclosure may also include tangible, non-transitory computer-readable storage media, or both tangible and non-transitory computer-readable storage media for carrying or having computer-executable instructions or data structures stored thereon. Such non-transitory computer-readable storage media can be any available media that can be accessed by a general purpose or special purpose computer, including the functional design of any special purpose processor as discussed above. By way of example, and not limitation, such non-transitory computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to carry or store desired program code means in the form of computer-executable instructions, data structures, or processor chip design. When information is transferred or provided over a network or another communications connection (either hardwired, wireless, or combination thereof) to a computer, the computer properly views the connection as a computer-readable medium. Thus, any such connection is properly termed a computer-readable medium. Combinations of the above should also be included within the scope of the computer-readable media. 
     Implementations herein can include the execution of computer-executable instructions of the method steps described in  FIGS. 10-12 . For example, computer-executable instructions can include instructions and data which cause a general purpose computer, special purpose computer, or special purpose processing device to perform a certain function or group of functions. Computer-executable instructions also include program modules that are executed by computers in stand-alone or network environments. Generally, program modules include routines, programs, components, data structures, objects, and the functions inherent in the design of special-purpose processors, etc. that perform particular tasks or implement particular abstract data types. Computer-executable instructions, associated data structures, and program modules represent examples of the program code means for executing steps of the methods disclosed herein. The particular sequence of such executable instructions or associated data structures represents examples of corresponding acts for implementing the functions described in such steps. 
     Those of skill in the art will appreciate that other examples of the disclosure may be practiced in network computing environments with many types of computer system configurations, including personal computers, hand-held devices, multi-processor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, and the like. Examples may also be practiced in distributed computing environments where tasks are performed by local and remote processing devices that are linked (either by hardwired links, wireless links, or by a combination thereof) through a communications network. In a distributed computing environment, program modules can be located in both local and remote memory storage devices. 
     The various implementations described above are non-limiting examples. For example, the principles herein apply not only to a smartphone device but to other devices capable of receiving communications such as a laptop computer. Various modifications and changes that can be made according to the principles described herein without departing from subject matter of the following claims.