Apparatus and method for performing image color transformation based on fovea rendering

Abstract

An apparatus comprising: a first color transformation subsystem configured to color transform a first region of an input image to generate a first color transformed sub-image; a second color transformation subsystem configured to color transform a second region of the input image to generate a second color transformed sub-image; and an image combiner configured to combine the first color transformed sub-image and the second color transformed sub-image to generate an output image.

Description

Technical Field

[0001] Generally speaking, aspects of the present disclosure relate to image processing, and more particularly, aspects of the present disclosure relate to apparatus and methods for performing image color transformation based on foveated rendering. Background Art

[0002] Color transformation is the process of transforming the color information of a source or input image into new color information for an output image for display purposes. Color transformation generally improves the accuracy of the colors produced by an associated display (e.g., a display of a mobile device, smartphone, or XR viewer (e.g., virtual reality (VR), augmented reality (AR), or other device, where X is a variable representing the type of reality viewer)). Color transformation can also be performed to produce specific visual effects for images rendered by the display (e.g., movies, renovations, animations, pseudo black and white, or other effects that can also be user-controllable). Color transformation is often employed to enhance the user experience associated with a device (e.g., a mobile device, smartphone, XR viewer, or other device). Summary of the Invention

[0003] The following is a simplified overview of one or more implementations to provide a basic understanding of such implementations. This overview is not an extensive overview of all contemplated implementations and is intended to neither identify key or important elements of all implementations nor identify the scope of any or all implementations. Its sole purpose is to present some concepts of one or more implementations in a simplified form as a prelude to the more detailed description that is presented later.

[0004] One aspect of the present disclosure relates to an apparatus comprising: a first color transform subsystem configured to perform a color transform on a first region of an input image to generate a first color-transformed sub-image; a second color transform subsystem configured to perform a color transform on a second region of the input image to generate a second color-transformed sub-image; and an image combiner configured to combine the first color-transformed sub-image and the second color-transformed sub-image to generate an output image.

[0005] Another aspect of the present disclosure relates to a method comprising: performing a color transform on a first region of an input image to generate a first color-transformed sub-image; performing a color transform on a second region of the input image to generate a second color-transformed sub-image; and combining the first color-transformed sub-image and the second color-transformed sub-image to generate an output image.

[0006] To accomplish the foregoing and related ends, one or more implementations include the features hereinafter fully described and particularly pointed out in the claims. The following description and the accompanying drawings set forth in detail certain illustrative aspects of one or more implementations. However, these aspects are indicative of but a few of the various ways in which the principles of various implementations may be employed, and the described implementations are intended to include all such aspects and their equivalents. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] Figure 1 A block diagram of an example apparatus for performing color transformation according to one aspect of the present disclosure is shown.

[0008] Figure 2 A block diagram is shown of another example apparatus for performing color transformation according to another aspect of the disclosure.

[0009] Figure 3A A diagram illustrating example images according to another aspect of the disclosure.

[0010] Figure 3B Another aspect of the present disclosure is shown for performing Figure 3A Block diagram of an example apparatus for color transformation of an image.

[0011] Figure 4A A diagram illustrating another example image according to another aspect of the disclosure.

[0012] Figure 4B Another aspect of the present disclosure is shown for performing Figure 4A Block diagram of an example apparatus for color transformation of an image.

[0013] Figure 5A A diagram illustrating another example image according to another aspect of the disclosure.

[0014] Figure 5B Another aspect of the present disclosure is shown for performing Figure 5A Block diagram of an example apparatus for color transformation of an image.

[0015] Figure 6 A block diagram is shown of another example apparatus for performing color transformation according to another aspect of the disclosure.

[0016] Figure 7 A perspective view of an example wearable device (e.g., augmented reality (AR) glasses) is shown according to another aspect of the present disclosure.

[0017] Figure 8 A block diagram of an example personal area network (PAN) is shown according to another aspect of the present disclosure.

[0018] Figure 9 A flowchart illustrating an example method of performing a color transformation by an example wearable device according to another aspect of the present disclosure is shown.

[0019] Figure 10 A flowchart illustrating another example method of performing a color transformation by an example wearable device according to another aspect of the present disclosure is shown.

[0020] Figure 11 A flowchart illustrating another example method of performing a color transformation by an example companion device on behalf of an example wearable device according to another aspect of the present disclosure is shown.

[0021] Figure 12 A flowchart illustrating another example method of performing a color transform of an input image according to another aspect of the disclosure is shown.

[0022] Figure 13 A flow chart illustrating another example apparatus for performing a color transform of an input image according to another aspect of the disclosure is shown. DETAILED DESCRIPTION

[0023] The detailed description set forth below in conjunction with the accompanying drawings is intended as a description of various configurations and is not intended to represent the only configuration in which the concepts described herein may be practiced. The detailed description includes specific details for the purpose of providing a thorough understanding of the various concepts. However, it will be apparent to those skilled in the art that these concepts may be practiced without these specific details. In some cases, well-known structures and components are shown in block diagram form to avoid obscuring such concepts.

[0024] Color transformation is the process of transforming the color information of a source or input image into new color information of an output image for display purposes. Color transformation generally improves the accuracy and / or effect of the colors produced by an associated display (e.g., a display of a mobile device, smartphone, or XR viewer (e.g., virtual reality (VR), augmented reality (AR), or other device, where X is a variable representing the type of reality viewer)). Color transformation can also be performed to produce specific visual effects for images rendered by the display (e.g., movies, renovations, animations, pseudo black and white, or other effects that can also be user-controllable). Color transformation is often employed to enhance the user experience with an associated device (e.g., a mobile device, smartphone, XR viewer, or other device).

[0025] Figure 1 A block diagram of an example apparatus 100 for performing color transforms according to one aspect of the present disclosure is shown. The apparatus 100 may include an image statistics analyzer 110, a color transform (CT) lookup table (LUT) generator 120, and a color transform mapper / interpolator 130.

[0026] The image statistics analyzer 110 includes a first input configured to receive a source image or input image, and a second input configured to receive one or more image parameters associated with the input image. The one or more image parameters may include dimensions (e.g., height and width) of the input image and other metadata. The image statistics analyzer 110 is configured to use the one or more image parameters to generate image statistics related to the input image. For example, the image statistics may provide tonal (distribution) information of the input image in the form of an image histogram.

[0027] The image histogram includes a set of different tone bins, which includes a relatively dark tone bin, a medium tone bin, and a subset of bright tone bins. Associated with the set of tone bins, the image histogram can provide the number of pixels of the input image corresponding to the set of different tone bins. For example, if the input image depicts a relatively dark scene, the corresponding image histogram can include a high number of pixels for the subset of relatively dark tone bins, a lower number of pixels for the subset of medium tone bins, and an even lower number of pixels for the subset of bright tone bins. Similarly, if the input image depicts a relatively bright scene, the corresponding image histogram can include a low number of pixels for the subset of relatively dark tone bins, a higher number of pixels for the subset of medium tone bins, and an even higher number of pixels for the subset of bright tone bins.

[0028] The CT LUT generator 120 is configured to generate a color transform (CT) lookup table (LUT) based on the image statistics information received from the image statistics analyzer 110. Considering some examples, if the image statistics indicate that the input image depicts a relatively dark scene, the CT LUT generator 120 may generate a CT LUT that generally brightens the input image. Conversely, if the image statistics indicate that the input image depicts a relatively bright scene, the CT LUT generator 120 may generate a CT LUT that generally darkens the input image. If the image statistics indicate that the input image depicts a medium-brightness scene, the CT LUT generator 120 may generate a CT LUT that expands or provides more contrast tonal components of the input image.

[0029] The generated CT LUT can be a three-dimensional (3D) or four-dimensional (4D) lookup table. For example, a 3D LUT can include the red, green, blue (RGB) hue components of each pixel of the input image as input. The 3D LUT maps the RGB value of each pixel of the input image to a new RGB value for each corresponding pixel of the output image. In addition to RGB, a 4D LUT can add a gamma or brightness (γ) component to map the RGBγ of each pixel of the input image to a new RGBγ value for each corresponding pixel of the output image. Other CT LUTs can transform other tonal parameters such as hue, saturation, brightness, and contrast. The RGB or RGBγ output values ​​of the LUT are indexed by the RGB or RGBγ values ​​of the input image, respectively.

[0030] The size of the CT LUT determines the accuracy or tonal resolution of the color transform. For example, a 3x3x3 CT LUT, the RGB value of each pixel is indexed into one of three (3) by three (3) by three (3) indices of the CT LUT. Thus, a 3x3x3 may be a relatively low tonal resolution CT LUT. A relatively high tonal resolution CT LUT may have a size of 1024x1024x1024x120, where the RGB gamma of each pixel is mapped to one of 1024 by 1024 by 1024 by 120 indices. For example, an XR viewer may require a higher tonal resolution color transform than a smartphone; and therefore, an XR viewer may have a CT LUT of much larger size and / or more dimensions than a smartphone.

[0031] The CT mapper / interpolator 130 can be configured to perform a color transform on the input image to generate an output image based on the CT LUT generated by the CT LUT generator 120, one or more image parameters associated with the input image, and one or more control parameters that can be set for interpolation to perform the color transform. As discussed, the size of the generated CT LUT can be a fixed size (e.g., 3x3x3, 17x17x17, 1024x1024x1024x120, etc.). Because the size of the CT LUT is fixed, a set of RGB or RGBγ value ranges is used to index the RGB or RGBγ output values ​​of the CT LUT to generate the output image. Since the value range is indexed to a specific value, interpolation can be used to obtain more accurate RGB or RGBγ values ​​for the pixels of the output image.

[0032] One option may be to perform no interpolation and use a specific output value for the entire range of input values. Another option may be to perform trilinear or quadlinear interpolation based on the input RGB or RGBγ values ​​indexed relative to the CT LUT. Yet another option may be to perform other types of interpolation based on the input RGB or RGBγ values ​​indexed relative to the CT LUT. As discussed, one or more control parameters may be used to select the specific interpolation (or no interpolation) to be performed to achieve the color transform. The computational processing power and power consumption of the CT mapper / interpolator 130 depend on the interpolation option selected, which may be controlled using one or more control parameters. The output image may then be provided to a display buffer for subsequent display of the output image.

[0033] One drawback is that the size or accuracy (tonal resolution) of the CT LUT is selected to optimize the color transformation for the foveal region of the image, while also considering the hardware and power resources required to implement the CT LUT. The foveal region of the image is where the user's eyes are directly focused, not the peripheral areas of the image. The foveal region of the image provides the user with the most focused and high-detail area of ​​the image, considering the human visual system. The peripheral areas of the image are generally out of focus and provide the user with less visual acuity than the foveal region. Therefore, because the CT LUT is selected to optimize the color transformation for the foveal region of the image (also considering the hardware and power resources), the accuracy of the selected CT LUT is significantly greater than the accuracy required to perform color transformation for the peripheral areas of the input image. Therefore, there is a waste of hardware and power resources when performing color transformation for the peripheral areas of the input image.

[0034] Another disadvantage is that the device 100 uses a LUT approach to perform color transformations. That is, in the LUT approach, the size or tonal resolution of the LUT is typically fixed based on the product in which the LUT is employed. For example, if a LUT is employed in a smartphone, the LUT may have a relatively small size because high-precision color transformations may not be required. On the other hand, if a LUT is employed in an XR viewer, the LUT may have a relatively large size because higher-precision color transformations may be desired or required. However, this approach is generally not scalable. For example, if a new version of a product is introduced that requires higher color transformation accuracy (e.g., it uses images with higher tonal resolution or color depth (e.g., 12 bits compared to 8 bits)), the LUT used on the previous version of the product may not be able to perform the desired color transformation. Therefore, a new LUT hardware design will be required.

[0035] Instead of the LUT approach, which may not scale easily as discussed, a software-driven computation-based approach (e.g., performed by a general-purpose processor, central processing unit (CPU), graphics processing unit (GPU), digital signal processor (DSP), data processing unit (DPU), etc.) may be employed, where only software updates may be provided to handle new color transformation requirements; thereby making the solution more scalable. However, employing a computation-based approach to perform color transformation on the entire image may consume a large amount of computing power, high power consumption, and may not perform the color transformation in real time or in sufficient time.

[0036] Figure 2 A block diagram of another example apparatus 200 for performing color transformation according to another aspect of the present disclosure is shown. Briefly, apparatus 200 employs an image separator to separate a relatively high acuity (HA) region (e.g., the foveal region) from a relatively low acuity (LA) region (e.g., the peripheral region) of a source or input image. A higher tonal resolution color transformation is performed on the HA region of the input image, and a lower tonal resolution color transformation is performed on the LA region of the input image. Apparatus 200 also employs an image combiner to combine the color-transformed HA sub-image with the color-transformed LA sub-image to generate an output image.

[0037] Specifically, the apparatus 200 includes a HA / LA image separator 210, a higher-resolution color conversion subsystem 220, a lower-resolution color conversion subsystem 230, and an image combiner 240. The HA / LA image separator 210 is configured to receive a source image or input image and separate therefrom an HA region (e.g., a foveal region) of the input image and an LA region (e.g., a peripheral region) of the input image. The higher-resolution color conversion subsystem 220 is configured to perform a color conversion on the HA region of the input image to generate a color-converted HA sub-image (CT-HA). The lower-resolution color conversion subsystem 230 is configured to perform a color conversion on the LA region of the input image to generate a color-converted LA sub-image (CT-LA). It should be understood that the HA / LA image separator 210 may be optional, as the input image may be internally filtered by subsystems 220 and 230 to generate HA and LA regions, respectively.

[0038] As some examples, the higher-resolution color transform subsystem 220 may utilize a computation-based color transform (e.g., a CPU, GPU, DSP, DPU, general-purpose processor, etc.), which has the advantage of being updatable via software updates and, thus, scalable with new product iterations. Since the HA region may be a small portion of the input image, performing a computation-based color transform on the HA region may not require significant computational power and power consumption and may be performed in real-time or in a time-acceptable manner. Since the higher-resolution color transform subsystem 220 can perform the color transform computationally, a higher tonal (color depth) granularity or precision color transform may be achieved compared to the lower-resolution color transform subsystem 230.

[0039] On the other hand, the lower-resolution color transform subsystem 230 can use a LUT to perform a color transform on the LA region of the input image. As discussed, a high-tonal-resolution color transform may not be necessary for the LA region because it may be associated with the peripheral regions of the input image, which the user's visual system perceives as not focusing on lower higher-frequency components or image sharpness. Therefore, from a user experience perspective, newer product iterations with higher color depth may not affect the LA region, and a LUT-based color transform approach for the LA region may be sufficient. It should be understood that the higher-resolution color transform subsystem 220 can also employ a LUT-based color transform approach, but with a higher size / precision / tonal resolution and a more dimensional color transform LUT.

[0040] Image combiner 240 is configured to receive and combine the color-transformed HA sub-image (CT-HA) and the color-transformed LA sub-image (CT-LA) to generate an output image. The output image can be provided to a display subsystem for display. Thus, the color transform provided by apparatus 200 can be scalable with respect to the HA region; can be configured to perform higher tonal resolution and precision transforms to achieve improved output images; and can utilize a lower-resolution LUT-based approach that is more suitable for the LA region from a hardware and power consumption perspective. Various examples of more detailed and / or variations of apparatus 200 are described below.

[0041] Figure 3AA diagram of an example image 300 according to another aspect of the present disclosure is shown. The image 300 can be an example source or input image on which a color transform is to be performed. The image 300 can be subdivided into an array of tiles (e.g., square or rectangular sets of pixels). In this example, the image 300 can be subdivided into seven (7) rows and nine (9) columns of tiles. For example, tiles T11 to T19 (where the first suffix (e.g., "1") represents a row and the second suffix (e.g., 1-9) represents a column) are located in the first row of tiles; tiles T21 to T29 are located in the second row of tiles; tiles T31 to T39 are located in the third row of tiles; and so on, until tiles T71 to T79 are located in the seventh row of tiles.

[0042] If the user's eye is focused on the center of image 300, the foveal region of image 300 may include tiles T34-T36, T44-T46, and T54-T56, as indicated by the dark shaded tiles with thick lines outlining the foveal region (convention used herein). When the user's eye is focused on the center of image 300, the peripheral region of image 300 may include those tiles outside the foveal region. For example, the first two rows T11-T29 and the last two rows T61-T79 are in the peripheral region of image 300. The tiles in the left three columns and three middle rows T31-T33, T41-T43, and T51-T53 and the right three columns and three middle rows T37-T39, T47-T49, and T57-T59 may also be in the peripheral region of image 300. Therefore, with respect to the device 200, the central foveal areas T34-T36, T44-T46, and T54-T56 may correspond to the HA area of ​​the input image, and the peripheral areas T11-T29, T31-T33, T41-T43, T51-T53, T37-T39, T47-T49, T57-T59, and T61-T79 may correspond to the LA area of ​​the input image.

[0043] Figure 3B A block diagram of an example apparatus 350 for performing a color transform on an image 300 according to another aspect of the present disclosure is shown. Apparatus 350 can be configured to perform a color transform on a source or input image where the HA or foveal area is located in a fixed, predefined region of the image. This has the advantage of simplifying the image separator, but may have the disadvantage of compromising the accuracy of the color transform because the user may not have their eyes focused on the center of the image.

[0044] Specifically, the apparatus 350 includes a foveal / peripheral image separator 360, a higher tone resolution color transform subsystem 370, a lower tone resolution color transform subsystem 380, and an image combiner 390. The foveal / peripheral image separator 360 is configured to receive a source image or input image 300 and separate therefrom a foveal (F) region (e.g., T34-T36, T44-T46, and T54-T56) of the input image and a peripheral (P) region (e.g., T11-T29, T31-T33, T41-T43, T51-T53, T37-T39, T47-T49, T57-T59, and T61-T79) of the input image 300. It should be understood that the foveal / peripheral image separator 360 may be optional, as the input image may be filtered internally by subsystems 370 and 380 to generate the foveal (F) and peripheral (P) regions, respectively.

[0045] A higher-resolution color transform subsystem 370, which may be implemented according to the previously discussed higher-resolution color transform subsystem 220, is configured to perform a color transform on the foveal (F) region of the input image 300 to generate a color-transformed foveal (F) sub-image (CT-F). A lower-resolution color transform subsystem 380, which may be implemented according to the previously discussed higher-resolution color transform subsystem 230, is configured to perform a color transform on the peripheral (P) region of the input image 300 to generate a color-transformed peripheral (P) sub-image (CT-P). An image combiner 390 is configured to combine the color-transformed foveal image (CT-F) with the color-transformed peripheral sub-image (CT-P) to generate an output image.

[0046] Figure 4A A diagram of another example image 400 according to another aspect of the present disclosure is shown. In this example, the high acuity (HA) or fovea (F) region can be dynamic, as the user's eyes can focus on different areas of the image 400 at different times. The image 400 can be subdivided into tiles as in the previously discussed image 300.

[0047] In this example, at time t1, the user may be viewing the lower right region of image 400. At this time, the HA or foveal (F) region may correspond to tiles T57-T59, T67-T69, and T77-T79, and the LA or peripheral (P) region may correspond to tiles T11-T49, T51-T56, T61-T66, and T71-T76. At time t2, the user may be viewing the top middle region of image 400. At this time, the HA or foveal (F) region may correspond to tiles T14-T16, T24-T26, and T34-T36, and the LA or peripheral (P) region may correspond to tiles T11-T13, T17-T19, T21-T23, T27-T29, T31-T33, T37-T39, and T41-T79. Then, at time t3, the user may be viewing the left middle region of image 400. At this point, the HA or foveal (F) region may correspond to tiles T32-T34, T42-T44, and T52-T54, and the LA or peripheral (P) region may correspond to tiles T1-T29, T31, T35-T39, T41, T45-T49, T51, T55-T59, and T61-T79. With a dynamic HA or foveal (F) region, the image separator of the color shifting device may need to perform image separation based on the position of the user's eyes, as discussed in more detail below.

[0048] Figure 4B A block diagram of an example apparatus 420 for performing a color transform on an image 400 according to another aspect of the present disclosure is shown. The apparatus 420 can be configured to perform a color transform on a source or input image 400 in which the HA or foveal area is dynamic. This has the advantage of achieving a higher precision color transform compared to the apparatus 350 that performs a color transform on an image in which the HA or foveal area is fixed.

[0049] Specifically, the apparatus 420 includes a foveal / peripheral image separator 430, an eye tracker 440, a higher-resolution color transformation subsystem 450, a lower-resolution color transformation subsystem 460, and an image combiner 470. The foveal / peripheral image separator 430 is configured to receive a source image or input image 400 and separate therefrom a foveal (F) region of the input image 400 and a peripheral (P) region of the input image 400 based on the eye position of the user detected by the eye tracker 440.

[0050] Considering the example of the input image 400 discussed previously, at time t1, the eye tracker 440 provides an eye position signal to the fovea / periphery separator 430, which indicates that the current HA or fovea (F) region corresponds to tiles T57-T59, T67-T69, and T77-T79, and the LA or peripheral (P) region corresponds to tiles T11-T49, T51-T56, T61-T66, and T71-T76. Therefore, the fovea / periphery separator 430 separates the HA or fovea (F) region and the LA or peripheral (P) region accordingly.

[0051] At time t2, the eye tracker 440 provides an eye position signal to the fovea / periphery separator 430, which indicates that the current HA or fovea (F) region corresponds to tiles T14-T16, T24-T26, and T34-T36, and the LA or periphery (P) region corresponds to tiles T11-T13, T17-T19, T21-T23, T27-T29, T31-T33, T37-T39, and T41-T79. Therefore, the fovea / periphery separator 430 separates the HA or fovea (F) region and the LA or periphery (P) region accordingly.

[0052] At time t3, the eye tracker 440 provides an eye position signal to the fovea / periphery separator 430, which indicates that the current HA or fovea (F) region corresponds to tiles T32-T34, T42-T44, and T52-T54, and the LA or periphery (P) region corresponds to tiles T11-T29, T31, T35-T39, T41, T45-T49, T51, T55-T59, and T61-T79. Therefore, the fovea / periphery separator 430 separates the HA or fovea (F) region and the LA or periphery (P) region accordingly.

[0053] It should be understood that foveal / peripheral image separator 430 may be optional, as the input image may be filtered internally by subsystems 450 and 460 to produce foveal (F) and peripheral (P) regions, respectively, based on the eye position signal generated by eye tracker 440. In this case, eye tracker 440 is coupled to subsystems 450 and 460.

[0054] The higher-resolution color conversion subsystem 450, which may be implemented according to the previously discussed higher-resolution color conversion subsystem 220, is configured to color-convert the foveal (F) region of the input image 400 at times t1, t2, and t3, respectively, to generate color-converted foveal (F) sub-images (CT-F). The lower-resolution color conversion subsystem 460, which may be implemented according to the previously discussed higher-resolution color conversion subsystem 230, is configured to color-convert the peripheral (P) region at times t1, t2, and t3, respectively, to generate color-converted peripheral (P) sub-images (CT-P). The image combiner 470 is configured to combine the color-converted foveal images (CT-F) corresponding to times t1, t2, and t3, respectively, with the color-converted peripheral sub-images (CT-P) to generate an output image.

[0055] Figure 5A A diagram of another example image 500 according to another aspect of the present disclosure is shown. In the previous example images 300 and 400, two different regions were identified: the HA or foveal (F) region and the LA or peripheral (P) region. However, it should be understood that separate color transforms with different resolutions / hardware can be performed on a set of regions of a source or input image. Image 500 is an example of such an input image with a set of regions that can be processed differently to achieve a color transform of the input image to generate an output image.

[0056] Image 500 can be subdivided into tiles T11-T79 in the same manner as previously discussed images 300 and 400. In this example, image 500 includes a first (central) region (the darkest shaded region) corresponding to tiles T34-T36, T44-T46, and T54-T56. Image 500 also includes a second (annular) region (the medium shaded region) surrounding the first (central) region corresponding to tiles T23-T27, T33, T37, T43, T47, T53, T57, and T63-T67. Image 500 further includes a third region (the lightest shaded region) generally surrounding the second region corresponding to tiles T13-T17, T31-T32, T38-T39, T41-T42, T48-T49, T51-T52, T58-T59, and T73-T77. Also, the image 500 includes fourth regions (non-shaded regions) at the four (4) corners of the image corresponding to tiles T11-T12, T21-T22, T18-T19, T28-T29, T61-T62, T71-T72, T68-T69, T78-T79.

[0057] The first (central) region may correspond to the foveal region, which may be processed using the highest tone resolution color transform process / hardware. A second region may be processed using a second highest tone resolution color transform process / hardware, which may be a peripheral region closest to the foveal region. A third region may be processed using a third highest tone resolution color transform process / hardware, which may be further from the foveal region than the second region. Furthermore, a fourth region may be processed using a fourth highest tone resolution color transform process / hardware, which may be farthest from the foveal region. It should be understood that these regions may be fixed or dynamic, depending on the position of the user's eyes.

[0058] Figure 5B A diagram of an example apparatus 520 for performing a color transform on an image 500 according to another aspect of the present disclosure is shown. The apparatus 520 includes an image separator 530, an optional eye tracker 540, a first resolution RES-1 (e.g., highest) color transform subsystem 550-1, a second resolution RES-2 (e.g., second highest) color transform subsystem 550-2, a third resolution RES-3 (e.g., third highest) color transform subsystem 550-3, a fourth resolution RES-4 (e.g., fourth highest or lowest) color transform subsystem 550-4, and an image combiner 560.

[0059] The image region separator 530 is configured to receive a source image or input image 500 and separate the input image 500 into a first region A1 (e.g., tiles T34-T36, T44-T46, and T54-T56), a second region A2 (e.g., tiles T23-T27, T33, T37, T43, T47, T53, T57, and T63-T67), a third region A3 (e.g., tiles T44-T46, and T54-T56), and a fourth region A4 (e.g., tiles T44-T46, and T54-T56). The image region separator 530 may perform separation based on an eye position signal generated by an optional eye tracker 540; in this case, the tiles corresponding to regions A1-A4 may vary.

[0060] It should be understood that the foveal / peripheral image separator 530 may be optional, as the input image may be filtered internally by subsystems 550-1 through 550-4 to produce regions A1 through A4, respectively, and optionally based on eye position signals generated by the optional eye tracker 540. In this case, the optional eye tracker 540 is coupled to subsystems 550-1 through 550-4.

[0061] The first resolution RES-1 (e.g., highest) color conversion subsystem 550-1 is configured to perform color conversion on a first area A1 of the input image 500 to generate a first color-converted sub-image (CT-A1). The second resolution RES-2 (e.g., second-highest) color conversion subsystem 550-2 is configured to perform color conversion on a second area A2 of the input image 500 to generate a second color-converted sub-image (CT-A2). The third resolution RES-3 (e.g., third-highest) color conversion subsystem 550-3 is configured to perform color conversion on a third area A3 of the input image 500 to generate a third color-converted sub-image (CT-A3). Furthermore, the fourth resolution RES-4 (e.g., fourth-highest or lowest) color conversion subsystem 550-4 is configured to perform color conversion on a fourth area A4 of the input image 500 to generate a fourth color-converted sub-image (CT-A4). The image combiner 560 is configured to combine the color-converted sub-images CT-A1 to CT-A4 to generate an output image.

[0062] Figure 6 A block diagram of another example apparatus 600 for performing color transforms according to one aspect of the present disclosure is shown. The apparatus 600 can be configured to perform a color transform on a source or input image, wherein the HA or foveal area is processed by a computation-based color transform subsystem and the LA or peripheral area is processed by a LUT-based color transform subsystem.

[0063] Specifically, the apparatus 600 includes a HA / LA image separator 610, a computation-based color transformation subsystem 620 (e.g., a CPU, GPU, DSP, DPU, etc.), a LUT-based color transformation subsystem 630, and an image combiner 640. The HA / LA image separator 610 is configured to receive a source image or an input image and separate the input image into an HA region and an LA region. The computation-based color transformation subsystem 620 is configured to perform a color transformation on the HA region of the input image to generate a color-transformed HA sub-image (CT-HA). The LUT-based color transformation subsystem 630 is configured to perform a color transformation on the LA region of the input image to generate a color-transformed LA sub-image (CT-LA). The image combiner 640 is configured to combine the color-transformed HA sub-image (CT-HA) with the color-transformed LA sub-image (CT-LA) to generate an output image.

[0064] It should be understood that HA / LA image separator 610 may be optional, as the input image may be filtered internally by subsystems 620 and 630 to produce HA and LA regions. Although not shown, apparatus 600 may also include an eye tracker coupled to HA / LA separator 610 or subsystems 620 and 630, as previously discussed in detail.

[0065] Figure 7 A perspective view of an example wearable device 700 (e.g., augmented reality (AR) viewer or glasses) according to another aspect of the present disclosure is shown. AR glasses 700 are an example of a wearable device. It should be understood that the wearable devices described herein can take many different forms, such as other types of viewers or glasses (e.g., virtual reality (VR) viewers or glasses), fitness measurement and tracking devices, health monitoring devices, medical devices, smart watches, earpieces, etc.

[0066] The AR glasses 700 may include a set of skin temperature sensors 705, 710, and 715. The skin temperature sensor 705 may be located on the right temple of the AR glasses 700. The skin temperature sensor 710 may be located on the left temple of the XR glasses 700. The skin temperature sensor 715 may be positioned on the inner nose bridge of the AR glasses 700. The AR glasses 700 may also include a right six-degree-of-freedom (6DOF) camera 720 and a left 6DOF camera 725, which are generally forward-pointing and located on the outer right and left edges near the right and left hinges of the AR glasses 700, respectively. The AR glasses 700 may also include a right infrared (IR) LED 730 and a left IR LED 735, which are also generally forward-pointing and located near the outer right and left edges below the right 6DOF camera 720 and the left 6DOF camera 725, respectively. Additionally, the AR glasses 700 may include a video (e.g., red, green, blue (RGB)) camera 740 that points generally forward and is located on the external nose bridge of the AR glasses 700.

[0067] For eye tracking, the AR glasses 700 may include a right eye tracking camera 745 and a left eye tracking camera 750, which point in the direction of the user's right eye and left eye when the AR glasses are worn, and are located on the inner side of the right edge and the left edge, respectively. In addition, the AR glasses 700 may include a right infrared (IR) LED ring 755 and a left IR LED ring 760 (e.g., LEDs connected in series) for illuminating the right eye area and the left eye area of ​​the user when the AR glasses are worn, and are located along the inner surface of the right edge and the left edge, respectively. The AR glasses 700 may also include a right lens 765 and a left lens 770 that serve as a right display and a left display, respectively. It should be understood that the above-mentioned components, placements, and orientations are merely examples, and that such configurations of the AR glasses can take many different forms.

[0068] As discussed in further detail below, the AR glasses 700 can apply a color transform to one or more images captured by any of the AR glasses' cameras 720, 725, and 740. The AR glasses 700 can employ any of the color transform devices 200, 350, 420, 520, and 600 described herein. Alternatively or in addition, the AR glasses 700 can receive image data from a companion device (e.g., a smartphone) that may be part of a personal area network (PAN) with the AR glasses 700. The companion device may have already performed a color transform to generate the image data provided to the AR glasses 700. Thus, such a companion device can employ any of the color transform devices 200, 350, 420, 520, and 600 described herein.

[0069] Figure 8 A block diagram of an example personal area network (PAN) 800 according to another aspect of the present disclosure is shown. The PAN 800 includes a wearable device 810 (e.g., AR glasses) and a companion device 830 (e.g., a smartphone). The wearable device 810 includes a camera subsystem 812, a computing subsystem 814 (e.g., a CPU, GPU, DSP, DPU, general-purpose processor, etc.), a color transform (CT) lookup table (LUT) subsystem 816, a display subsystem 818, an eye tracker 820, and a communication interface 822, all of which are coupled together via one or more data buses (collectively, data buses 824). The communication interface 822 can be a wired and / or wireless communication interface, such as a wireless local area network (WLAN), WiFi, a wireless wide area network (WWAN), cellular, Bluetooth, etc.

[0070] As discussed in further detail herein, the camera subsystem 812 is configured to capture one or more images. The computation subsystem 814 may be configured to perform a computation-based color transform of a high acuity (HA) or foveal (F) region based on one or more images received from the camera subsystem 812 via a data bus 824 and, optionally, based on user eye position information generated by an eye tracker 820. The CT LUT subsystem 816 may be configured to perform a LUT-based color transform of a low acuity (LA) or peripheral (P) region based on one or more images received from the camera subsystem 812 via a data bus 824 and, optionally, based on user eye position information generated by an eye tracker 820.

[0071] The computing subsystem 814 can also be configured to combine the one or more color-converted HA or F sub-images or the one or more images with the one or more color-converted LA or P sub-images received from the CT LUT subsystem 816 via the data bus 824 to generate one or more output images, respectively. The display subsystem 818 can receive the one or more output images from the computing subsystem 814 via the data bus 824 for displaying the one or more output images. Alternatively or in addition, the wearable device 810 can employ the companion device 830 to perform color conversion on its behalf by sending image information to the companion device 830 via the communication interface 822.

[0072] The companion device 830 includes a communication interface 832, a computing subsystem 834 (e.g., a CPU, a GPU, a DSP, a DPU, a general purpose processor, etc.), and a color transform (CT) lookup table (LUT) subsystem 836, all of which are coupled together via a data bus 838. Similarly, the communication interface 832 can also be a wired and / or wireless communication interface, such as a wireless local area network (WLAN), WiFi, a wireless wide area network (WWAN), cellular, Bluetooth, etc.

[0073] The computation subsystem 834 may be configured to perform a computation-based color transform of the high acuity (HA) or foveal (F) region based on one or more images received from the wearable device 810 via the communication interface 832 and the data bus 838. Similarly, the CT LUT subsystem 836 may be configured to perform a LUT-based color transform of the low acuity (LA) or peripheral (P) region based on one or more images received from the wearable device 810 via the communication interface 832 and the data bus 838.

[0074] The computing subsystem 834 may also be configured to combine the one or more color-transformed HA or F sub-images or the one or more images with the one or more color-transformed LA or P sub-images received from the CT LUT subsystem 836 via the data bus 838 to generate one or more output images, respectively. The computing subsystem 834 may send the one or more output images to the wearable device 810 via the communication interface 832 for display purposes.

[0075] Figure 9 A flow chart illustrating an example method 900 of performing a color transform by an example wearable device 810 according to another aspect of the present disclosure is shown. For ease of explanation, the method 900 is described with respect to a single image, but it should be understood that the method 900 can be applied to a collection of images or a time sequence of images, such as in a video capture.

[0076] According to method 900, camera subsystem 812 captures an image (block 910). Method 900 also includes computing subsystem 814 performing a color transform on a first portion of the captured image or based on the captured image (block 920). For example, computing subsystem 814 may process the captured image for purposes other than color transforming, and computing subsystem 814 may then perform a color transform on the first portion of the processed image. Additionally, method 900 includes CT LUT subsystem 816 performing a color transform on a second portion of the captured image or based on the captured image (block 930). For example, CT LUT subsystem 816 may receive the processed image from computing subsystem 814 and may perform a color transform on the second portion of the processed image.

[0077] Method 900 also includes the computing subsystem 814 combining the first color-converted portion and the second color-converted portion to generate an output image (block 940). For example, the computing subsystem 814 may receive the color-converted second portion from the CT LUT subsystem 816 and then perform a combination of the second portion and the first portion to generate the output image. Then, according to method 900, the display subsystem 818 displays the output image (block 950).

[0078] Figure 10 A flow chart of another example method 1000 of performing a color transform by an example wearable device 810 according to another aspect of the present disclosure is shown. Similarly, for ease of explanation, the method 1000 is described with respect to a single image, but it should be understood that the method 1000 can be applied to a collection of images or a time sequence of images, such as in a video capture.

[0079] According to method 1000, computing subsystem 814 receives an image from companion device 830 via communication interface 822 (and data bus 824) (block 1010). Method 1000 also includes computing subsystem 814 performing a color transform on a first portion of, or based on, the received image (block 1020). Additionally, method 1000 includes CT LUT subsystem 816 performing a color transform on a second portion of, or based on, the received image (block 1030). For example, CT LUT subsystem 816 may receive an image from computing subsystem 814 via data bus 824 and may perform a color transform on the second portion of the received image.

[0080] Method 1000 also includes the computing subsystem 814 combining the first color-converted portion and the second color-converted portion to generate an output image (block 1040). For example, the computing subsystem 814 may receive the color-converted second portion from the CT LUT subsystem 816 via the data bus 824 and then combine the second portion with the first portion to generate the output image. Then, according to method 1000, the display subsystem 818 displays the output image (block 1050).

[0081] Figure 11 A flow chart is shown of another example method 1100 for performing a color transformation on behalf of an example wearable device 810 by an example companion device 830 according to another aspect of the present disclosure. As in the previous methods 900 and 1000, for ease of explanation, the method 1100 is described with respect to a single image, but it should be understood that the method 1100 can be applied to a collection of images or a time sequence of images, such as in a video capture.

[0082] According to method 1100, computing subsystem 834 receives image-based information from wearable device 810 via communication interface 832 (and data bus 838) (block 1110). For example, the image-based information may relate to pose information of one or more objects (e.g., a person's face or head) detected in an image captured by wearable device 810. Method 1100 also includes computing subsystem 834 generating an image based on the image-based information (block 1120). For example, the image may include graphical content (e.g., graphical glasses or a hat) to be added to the image captured by wearable device 810 (e.g., superimposing the glasses or hat on the person's face or head).

[0083] Method 1100 also includes the computing subsystem 834 performing a color transform on a first portion of the image or based on the image (block 1130). Additionally, method 1100 includes the CT LUT subsystem 836 performing a color transform on a second portion of the image or based on the image (block 1140). For example, the CT LUT subsystem 836 may receive the image from the computing subsystem 834 via the data bus 838 and may perform a color transform on the second portion of the image.

[0084] Method 1100 also includes the computing subsystem 834 combining the first color-converted portion and the second color-converted portion to generate an output image (block 1150). For example, the computing subsystem 834 may receive the color-converted second portion from the CT LUT subsystem 836 via the data bus 838 and then combine the second portion with the first portion to generate the output image. Then, according to method 1100, the computing subsystem 834 transmits the output image to the wearable device via the communication interface 832 (and the data bus 838) (block 1160).

[0085] Figure 12 A flow chart illustrating another example method 1200 for performing a color transform of an input image according to another aspect of the present disclosure is shown. The method 1200 includes performing a color transform on a first region of the input image to generate a first color-transformed sub-image (block 1210). The method 1200 also includes performing a color transform on a second region of the input image to generate a second color-transformed sub-image (block 1220). Additionally, the method 1200 includes combining the first color-transformed sub-image and the second color-transformed sub-image to generate an output image (block 1230).

[0086] Figure 13 A flow chart illustrating another example apparatus 1300 for performing color transformation of an input image according to another aspect of the present disclosure is shown. Apparatus 1300 includes a unit 1310 for color transforming a first region of the input image to generate a first color-transformed sub-image. Apparatus 1300 also includes a unit 1320 for color transforming a second region of the input image to generate a second color-transformed sub-image. Additionally, apparatus 1300 includes a unit 1330 for combining the first color-transformed sub-image and the second color-transformed sub-image to generate an output image.

[0087] Some components described herein (such as one or more of the subsystems, thermal controllers, and communication interfaces) may be implemented using a processor. As used herein, a processor may be any dedicated circuit, processor-based hardware, a processing core of a system on a chip (SOC), or the like. Hardware examples of a processor may include a microprocessor, a microcontroller, a digital signal processor (DSP), a field programmable gate array (FPGA), a programmable logic device (PLD), a state machine, gating logic, a discrete hardware circuit, and other suitable hardware configured to perform the various functions described throughout this disclosure.

[0088] The processor may be coupled to a memory (e.g., typically a computer-readable medium or media) such as a magnetic storage device (e.g., a hard disk, a floppy disk, a magnetic stripe), an optical disk (e.g., a compact disc (CD) or a digital versatile disc (DVD)), a smart card, a flash memory device (e.g., a card, stick, or key drive), a random access memory (RAM), a read-only memory (ROM), a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), registers, a removable disk, and any other suitable medium for storing software and / or instructions that can be accessed and read by a computer. The memory may store computer-executable code (e.g., software). Whether referred to as software, firmware, middleware, microcode, hardware description language, or other terms, software should be broadly construed to mean instructions, an instruction set, code, a code segment, program code, a program, a subroutine, a software module, an application, a software application, a software package, a routine, a subroutine, an object, an executable file, a thread of execution, a procedure / process, a function, and the like.

[0089] The following provides an overview of various aspects of the disclosure:

[0090] Aspect 1: An apparatus comprising: a first color transformation subsystem configured to perform a color transformation on a first region of an input image to generate a first color-transformed sub-image; a second color transformation subsystem configured to perform a color transformation on a second region of the input image to generate a second color-transformed sub-image; and an image combiner configured to combine the first color-transformed sub-image and the second color-transformed sub-image to generate an output image.

[0091] Aspect 2: An apparatus according to Aspect 1, wherein: the first color transformation subsystem is configured to perform color transformation on the first area of ​​the input image according to a first tone resolution; and the second color transformation subsystem is configured to perform color transformation on the second area of ​​the input image according to a second tone resolution, wherein the first tone resolution is higher than the second tone resolution.

[0092] Aspect 3: The apparatus according to aspect 1 or 2, wherein: the first color transformation subsystem comprises a calculation-based color transformation subsystem; and the second color transformation subsystem comprises a lookup table (LUT)-based color transformation subsystem.

[0093] Aspect 4: The apparatus according to aspect 1 or 2, wherein: the first color transformation subsystem comprises a first lookup table (LUT)-based color transformation subsystem; and the second color transformation subsystem comprises a second LUT-based color transformation subsystem.

[0094] Aspect 5: The apparatus of claim 4, wherein: the first LUT-based color transformation subsystem comprises a first LUT size; and the second LUT-based color transformation subsystem comprises a second LUT size, wherein the first LUT size is larger than the second LUT size.

[0095] Aspect 6: An apparatus according to Aspect 4 or 5, wherein: the first LUT-based color transformation subsystem includes a first LUT; and the second LUT-based color transformation subsystem includes a second LUT, wherein the dimension of the first LUT is greater than the dimension of the second LUT.

[0096] Aspect 7: An apparatus according to any one of Aspects 4-6, wherein: the first LUT-based color transformation subsystem is configured to apply interpolation of the first area of ​​the input image relative to the index of the first LUT to generate the first color-transformed sub-image; and the second LUT-based color transformation subsystem is configured to map the second area of ​​the input image to the index of the second LUT to generate the second color-transformed sub-image.

[0097] Clause 8: The apparatus according to any one of clauses 1 to 7, wherein: the first region comprises a foveal region of the input image; and the second region comprises a peripheral region of the input image.

[0098] Aspect 9: The apparatus according to aspect 8, wherein the foveal area and the peripheral area of ​​the input image are predefined fixed areas of the input image.

[0099] Aspect 10: The apparatus according to Aspect 8 further includes an eye tracker configured to generate an eye position signal indicating the position of the user's eyes, wherein the foveal area and the peripheral area of ​​the input image are based on the eye position signal.

[0100] Aspect 11: The apparatus according to any one of Aspects 1 to 10, further comprising an image separator configured to separate the first region and the second region of the input image.

[0101] Aspect 12: The apparatus according to Aspect 11 further includes an eye tracker, the eye tracker being configured to generate an eye position signal indicating the position of the user's eyes, wherein the image separator is configured to separate the first area and the second area of ​​the input image based on the eye position signal.

[0102] Aspect 13: The apparatus according to any one of Aspects 1-12 further includes at least one other color transformation subsystem, wherein the at least one other color transformation subsystem is configured to perform color transformation on at least one other region of the input image respectively to generate at least one other color-transformed sub-image, wherein the image combiner is configured to combine the at least one other color-transformed sub-image with the first color-transformed sub-image and the second color-transformed sub-image to generate the output image.

[0103] Clause 14: The apparatus of any one of Clauses 1-13, further comprising a camera subsystem configured to generate the input image or an image on which the input image is based.

[0104] Clause 15: The apparatus according to any one of clauses 1 to 14, further comprising a communication interface, wherein the input image or the image on which the input image is based is received from another apparatus via the communication interface.

[0105] Aspect 16: The apparatus according to any one of aspects 1-15, further comprising a display subsystem configured to display the output image.

[0106] Aspect 17: The apparatus according to any one of aspects 1-16, further comprising a communication interface, wherein the output image is sent to another apparatus via the communication interface.

[0107] Aspect 18: A method comprising: performing a color transform on a first region of an input image to generate a first color-transformed region of an output image; performing a color transform on a second region of the input image to generate a second color-transformed region of the output image; and combining the first color-transformed region and the second color-transformed region to generate the output image.

[0108] Aspect 19: A method according to Aspect 18, wherein: the color transformation of the first area of ​​the input image is based on a first tone resolution; and the color transformation of the second area of ​​the input image is based on a second tone resolution, wherein the first tone resolution is higher than the second tone resolution.

[0109] Aspect 20: A method according to Aspect 18 or 19, wherein: color transforming the first area includes performing calculations on color information associated with the first area to generate color information associated with the first color-transformed sub-image; and color transforming the second area includes using the color information associated with the second area to index a lookup table (LUT) to access color information associated with the second color-transformed sub-image.

[0110] Clause 21: The method according to any one of clauses 18 to 20, wherein: the first region comprises a foveal region of the input image; and the second region comprises a peripheral region of the input image.

[0111] Aspect 22: The method according to Aspect 21, further comprising: tracking the position of the user's eyes to identify the foveal area and the peripheral area of ​​the input image.

[0112] Aspect 23: A device comprising: a unit for performing a color transform on a first area of ​​an input image to generate a first color-transformed sub-image; a unit for performing a color transform on a second area of ​​the input image to generate a second color-transformed sub-image; and a unit for combining the first color-transformed sub-image and the second color-transformed sub-image to generate an output image.

[0113] Aspect 24: An apparatus according to Aspect 23, wherein: the unit for performing color transformation on the first area of ​​the input image performs color transformation according to a first tone resolution; and the unit for performing color transformation on the second area of ​​the input image performs color transformation according to a second tone resolution, wherein the first tone resolution is higher than the second tone resolution.

[0114] Aspect 25: An apparatus according to Aspect 23 or 24, wherein: the unit for performing color transformation on the first area includes a unit for performing calculations on color information associated with the first area to generate color information associated with the first color-transformed sub-image; and the unit for performing color transformation on the second area includes a unit for using the color information of the second area to index a lookup table (LUT) to access color information associated with the second color-transformed sub-image.

[0115] Clause 26: The apparatus according to any one of clauses 23-25, wherein: the first region comprises a foveal region of the input image; and the second region comprises a peripheral region of the input image.

[0116] Aspect 27: The apparatus according to Aspect 26, further comprising: a unit for tracking positions of eyes of a user to identify the foveal area and the peripheral area of ​​the input image.

[0117] The previous description of the present disclosure is provided to enable those skilled in the art to make or use the present disclosure. Various modifications to the present disclosure will be apparent to those skilled in the art, and the general principles defined herein may be applied to other variations without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the examples described herein, but rather to be given the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A device comprising: a first color transform subsystem configured to perform a color transform on a first region of an input image to generate a first color transformed sub-image; a second color transformation subsystem configured to perform a color transformation on a second region of the input image to generate a second color transformed sub-image; as well as An image combiner is configured to combine the first color converted sub-image and the second color converted sub-image to generate an output image.

2. The device according to claim 1, wherein: The first color transformation subsystem is configured to perform a color transformation on the first region of the input image according to a first tone resolution; and The second color transformation subsystem is configured to perform color transformation on the second region of the input image according to a second tonal resolution, wherein the first tonal resolution is higher than the second tonal resolution.

3. The device according to claim 1, wherein: The first color transformation subsystem comprises a computation-based color transformation subsystem; and The second color conversion subsystem includes a lookup table (LUT) based color conversion subsystem.

4. The device according to claim 1, wherein: The first color conversion subsystem comprises a first lookup table (LUT) based color conversion subsystem; and The second color conversion subsystem includes a second LUT-based color conversion subsystem.

5. The device according to claim 4, wherein: The first LUT-based color transformation subsystem includes a first LUT size; and The second LUT-based color transformation subsystem includes a second LUT size, wherein the first LUT size is larger than the second LUT size.

6. The device according to claim 4, wherein: The first LUT-based color transformation subsystem includes a first LUT; and The second LUT-based color transformation subsystem includes a second LUT, wherein a dimension of the first LUT is greater than a dimension of the second LUT.

7. The apparatus according to claim 4, wherein: the first LUT-based color transform subsystem being configured to apply interpolation of the first region of the input image relative to an index of a first LUT to generate the first color transformed sub-image; and The second LUT-based color transform subsystem is configured to map the second region of the input image to an index of a second LUT to generate the second color transformed sub-image.

8. The apparatus according to claim 1, wherein: The first region includes a fovea region of the input image; and The second area includes a peripheral area of ​​the input image.

9. The device according to claim 8, wherein The foveal area and the peripheral area of ​​the input image are predefined fixed areas of the input image.

10. The apparatus of claim 8, further comprising an eye tracker configured to generate an eye position signal indicative of a position of an eye of the user, wherein The foveal area and the peripheral area of ​​the input image are based on the eye position signal. 11 . The apparatus according to claim 1 , further comprising an image separator configured to separate the first region and the second region of the input image.

12. The apparatus of claim 11 , further comprising an eye tracker configured to generate an eye position signal indicative of a position of an eye of the user, wherein The image separator is configured to separate the first area and the second area of ​​the input image based on the eye position signal.

13. The apparatus according to claim 1 , further comprising at least one other color transformation subsystem, wherein the at least one other color transformation subsystem is configured to perform color transformation on at least one other region of the input image to generate at least one other color-transformed sub-image, respectively. The image combiner is configured to combine the at least one other color converted sub-image with the first color converted sub-image and the second color converted sub-image to generate the output image.

14. The apparatus of claim 1, further comprising a camera subsystem configured to generate the input image or an image on which the input image is based.

15. The apparatus according to claim 1, further comprising a communication interface, wherein The input image, or an image on which the input image is based, is received from another device via the communication interface.

16. The apparatus of claim 1, further comprising a display subsystem configured to display the output image.

17. The apparatus according to claim 1, further comprising a communication interface, wherein The output image is transmitted to another device via the communication interface.

18. A method comprising: performing a color transform on a first region of an input image to generate a first color-transformed sub-image; performing a color transform on a second region of the input image to generate a second color-transformed sub-image; as well as The first color converted sub-image and the second color converted sub-image are combined to generate an output image.

19. The method according to claim 18, wherein: performing a color transform on the first region of the input image is according to a first tonal resolution; and The color transforming of the second region of the input image is performed according to a second tonal resolution, wherein the first tonal resolution is higher than the second tonal resolution.

20. The method of claim 18, wherein: Color transforming the first region includes performing a calculation on color information associated with the first region to generate color information associated with the first color transformed sub-image; and Color transforming the second region includes using color information associated with the second region to index a lookup table (LUT) to access color information associated with the second color transformed sub-image.

21. The method of claim 18, wherein: The first region includes a fovea region of the input image; and The second area includes a peripheral area of ​​the input image.

22. The method according to claim 21, further comprising: The position of the user's eyes is tracked to identify the foveal area and the peripheral area of ​​the input image.

23. An apparatus comprising: means for color transforming a first region of an input image to generate a first color transformed sub-image; means for color transforming a second region of the input image to generate a second color transformed sub-image; as well as Means for combining the first color converted sub-image and the second color converted sub-image to generate an output image.

24. The apparatus of claim 23, wherein: The unit for color transforming the first region of the input image performs color transform according to a first tonal resolution; and The unit for color transforming the second area of ​​the input image performs color transform according to a second tonal resolution, wherein the first tonal resolution is higher than the second tonal resolution.

25. The apparatus of claim 23, wherein: The means for color transforming the first region includes means for performing calculations on color information associated with the first region to generate color information associated with the first color transformed sub-image; and The means for color converting the second region includes means for indexing a lookup table (LUT) using the color information of the second region to access color information associated with the second color converted sub-image.

26. The apparatus of claim 23, wherein: The first region includes a fovea region of the input image; and The second area includes a peripheral area of ​​the input image.

27. The apparatus according to claim 26, further comprising: Unit for tracking the position of the user's eyes to identify the foveal area and the peripheral area of ​​the input image.

Images