Techniques for utilizing gain maps to manage changing image conditions

Abstract

Various techniques for utilizing the gain map are disclosed. According to some embodiments, one technique for utilizing the gain map includes: (1) accessing an enhanced image including a high dynamic range (HDR) image and a gain map, (2) extracting the HDR image and the gain map from the enhanced image, (3) generating a standard dynamic range (SDR) image using the HDR image and the gain map, (4) receiving and applying first modification instructions to the HDR image, (5) generating second modification instructions based on at least the first modification instructions, (6) applying the second modification instructions to the SDR image, (7) generating a second gain map by comparing the HDR image to the SDR image or vice versa, and (8) embedding the second gain map into the HDR image or the SDR image.

Description

[Technical Field]

[0001] The embodiments described herein describe techniques for utilizing gain maps to manage changing conditions in an image. In particular, the gain maps can be utilized to provide various features, including generating a first version of the image and a second version of the image by utilizing the gain maps. [Background technology]

[0002] The dynamic range of an image refers to the range of pixel values ​​between the brightest and darkest parts of the image (often called "luminance"). In particular, conventional image sensors can only capture a limited range of luminance in a single exposure of a scene, at least relative to what the human eye can perceive from the same scene. In digital photography, this limited range is usually referred to as standard dynamic range (SDR).

[0003] Despite the limitations of image sensors mentioned above, improvements in photography techniques have made it possible to capture a wider range of light (referred to herein as high dynamic range (HDR)). This can be achieved by (1) capturing multiple "brackets" of images, i.e., images with different exposure times (also called "stops"), and then (2) fusing the bracketed images into a single image that incorporates different aspects of the different exposures. In this regard, a single HDR image has a wider dynamic range of luminance compared to what could otherwise be captured in each of the individual exposures. This makes HDR images superior to SDR images in some embodiments.

[0004] Display devices capable of displaying HDR images (in their true form) are becoming more accessible due to advances in design and manufacturing technologies. However, the majority of display devices currently in use (and continue to be manufactured) are only capable of displaying SDR images. Therefore, a device with an SDR-limited display that receives an HDR image must perform various tasks to convert (i.e., downgrade) the HDR image to an SDR image equivalent. Conversely, a device with an HDR-capable display that receives an SDR image may attempt to perform various tasks to convert (i.e., upgrade) the SDR image to an HDR image equivalent.

[0005] Unfortunately, the aforementioned conversion techniques typically produce inconsistent and / or undesirable results. In particular, downgrading an HDR image to an SDR image can introduce visual artifacts (e.g., banding) into the resulting image, which are often uncorrectable with additional image processing. Conversely, upgrading an SDR image to an HDR image involves applying various levels of inference, which may also introduce uncorrectable visual artifacts.

[0006] Therefore, what is needed is a technique that allows an image to be efficiently and accurately transitioned between different states. For example, it would be desirable to allow an HDR image to be downgraded to its true SDR counterpart (and vice versa) without relying on the aforementioned (and inadequate) conversion techniques. Summary of the Invention

[0007] Representative embodiments described herein disclose techniques for managing various states of an image using a gain map. In particular, the gain map can be used to provide various features, including generating a first version of the image and a second version of the image by using the gain map.

[0008] One embodiment describes a method for managing edits to different versions of an image using a gain map, including: (1) accessing an enhanced image including a high dynamic range (HDR) image and a gain map, (2) extracting the HDR image and the gain map from the enhanced image, (3) generating a standard dynamic range (SDR) image using the HDR image and the gain map, (4) receiving and applying first modification instructions to the HDR image, (5) generating second modification instructions based on at least the first modification instructions, (6) applying the second modification instructions to the SDR image, (7) generating a second gain map by comparing the HDR image to the SDR image or vice versa, and (8) embedding the second gain map into the HDR image or the SDR image.

[0009] Another embodiment describes a method for utilizing a gain map to manage output of an image on a display device, the method including: (1) accessing an enhanced image including a first version of the image and a gain map, (2) identifying a headroom level for a second version of the image based on a current brightness setting of the display device, (3) establishing a modified gain map based on the headroom level, (4) generating the second version of the image using the first version of the image and the modified gain map, and (5) displaying the second version of the image on the display device.

[0010] Yet another embodiment describes a method for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. The method includes: (1) accessing an HDR image, (2) generating an SDR image by applying a global tone mapping operation to the HDR image, (3) generating a gain map by comparing the SDR image with the HDR image, (4) embedding the gain map in the HDR image, (5) receiving a request to view an SDR version of the HDR image, and (6) utilizing the HDR image and the gain map to provide an SDR version of the HDR image.

[0011] Other embodiments include a non-transitory computer-readable storage medium configured to store instructions that, when executed by a processor included in the computing device, cause the computing device to perform various steps of any of the aforementioned methods. Further embodiments include a computing device configured to perform various steps of any of the aforementioned methods.

[0012] Other aspects and advantages of the present invention will become apparent from the following detailed description, taken in conjunction with the accompanying drawings, which illustrate, by way of example, the principles of the described embodiments.

[0013] The present disclosure will be readily understood by the following detailed description in conjunction with the accompanying drawings, in which like reference numerals indicate like structural elements, and in which: [Brief explanation of the drawings]

[0014] [Figure 1] 1 illustrates an overview of a computing device that can be configured to perform various techniques described herein, according to some embodiments.

[0015] [Figure 2A]1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2B] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2C] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2D] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2E] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2F] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2G] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments. [Figure 2H] 1A-1C illustrate a series of conceptual diagrams of a technique that utilizes gain maps to manage edits to different versions of an image, according to some embodiments.

[0016] [Figure 3A] 1A-1C are a series of conceptual diagrams of techniques that utilize gain maps to manage the output of images on a display device, according to some embodiments. [Figure 3B] 1A-1C are a series of conceptual diagrams of techniques that utilize gain maps to manage the output of images on a display device, according to some embodiments. [Figure 3C] 1A-1C are a series of conceptual diagrams of techniques that utilize gain maps to manage the output of images on a display device, according to some embodiments. [Figure 3D] 1A-1C are a series of conceptual diagrams of techniques that utilize gain maps to manage the output of images on a display device, according to some embodiments. [Figure 3E] 1A-1C are a series of conceptual diagrams of techniques that utilize gain maps to manage the output of images on a display device, according to some embodiments. [Figure 3F] 1A-1C are a series of conceptual diagrams of techniques that utilize gain maps to manage the output of images on a display device, according to some embodiments.

[0017] [Figure 4A] 1A-1C are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. [Figure 4B] 1A-1C are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. [Figure 4C] 1A-1C are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. [Figure 4D] 1A-1C are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. [Figure 4E] 1A-1C are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. [Figure 4F]1A-1C are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments.

[0018] [Figure 5] 1 shows a detailed diagram of a computing device that can be used to perform various techniques described herein, according to some embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0019] Representative examples of applications of the methods and apparatus according to the present application are described in this section. These examples are provided solely to add context and to aid in understanding the described embodiments. Thus, it will be apparent to one skilled in the art that the described embodiments may be practiced without some or all of these specific details. In other instances, well-known process steps have not been described in detail to avoid unnecessarily obscuring the described embodiments. Other applications are possible, and therefore the following examples should not be construed as limiting.

[0020] In the following detailed description, reference is made to the accompanying drawings which form a part of the description, and in which is shown by way of illustration specific embodiments in accordance with the described embodiments. These embodiments are described in sufficient detail to enable one skilled in the art to practice the described embodiments, but it is to be understood that these examples are not limiting, and that other embodiments may be used, and changes may be made without departing from the spirit and scope of the described embodiments.

[0021] Representative embodiments described herein disclose techniques for managing various states of an image using a gain map. In particular, the gain map may be used to provide various features, including generating a first version of the image and a second version of the image by using the gain map. A more detailed description of these techniques is provided below in connection with FIGS. 1, 2A-2H, 3A-3F, 4A-4F, and 5.

[0022] FIG. 1 illustrates an overview 100 of a computing device 102 that can be configured to perform various techniques described herein. As shown in FIG. 1, the computing device 102 can include a processor 104, a volatile memory 106, and a non-volatile memory 124. A more detailed breakdown of exemplary hardware components that may be included in the computing device 102 is illustrated in FIG. 5; note that these components are omitted from the illustration of FIG. 1 solely for simplicity. For example, the computing device 102 can include additional non-volatile memory (e.g., a solid-state drive, a hard drive, etc.), other processors (e.g., a multi-core central processing unit (CPU)), a graphics processing unit (GPU), etc.). According to some embodiments, an operating system (OS) (not shown in FIG. 1) can be loaded into the volatile memory 106, and the OS can execute various applications that collectively enable the various techniques described herein to be implemented. For example, these applications can include an image analyzer 110 (and its internal components), a gain map generator 120 (and its internal components), one or more compressors (not shown in FIG. 1), etc.

[0023] As shown in FIG. 1 , the volatile memory 106 can be configured to receive a multi-channel image 108. The multi-channel image 108 can be provided, for example, by a digital imaging unit (not shown in FIG. 1 ) configured to capture and process digital images. According to some embodiments, the multi-channel image 108 can be comprised of a collection of pixels, with each pixel in the collection of pixels including a group of sub-pixels (e.g., red sub-pixels, green sub-pixels, blue sub-pixels, etc.). It should be noted that the term “sub-pixel” as used herein can be synonymous with the term “channel.” It should also be noted that the multi-channel image 108 can have different resolutions, layouts, bit depths, etc. without departing from the scope of this disclosure.

[0024] According to some embodiments, a given multi-channel image 108 can represent a standard dynamic range (SDR) image constituting a single exposure of a scene collected and processed by the digital imaging unit. A given multi-channel image 108 can also represent a high dynamic range (HDR) image constituting multiple exposures of a scene collected and processed by the digital imaging unit. To generate an HDR image, the digital imaging unit may capture the scene under different exposure brackets, for example, three exposure brackets often referred to as “EV0,” “EV−,” and “EV+.” Generally, an EVO image corresponds to a normal / ideal exposure of the scene (typically captured using the digital imaging unit's auto-exposure setting). An EV− image corresponds to an underexposed image of the scene (e.g., four times darker than EV0), and an EV+ image corresponds to an overexposed image of the scene (e.g., four times brighter than EV0). The digital imaging unit can combine different exposures to generate a resultant image incorporating a wider range of brightness relative to an SDR image. Note that the multi-channel image 108 described herein is not limited to SDR / HDR images. Conversely, multi-channel image 108 may represent any form of digital image (eg, scanned image, computer-generated image, etc.) without departing from the scope of this disclosure.

[0025] 1 , the multi-channel image 108 may (optionally) be provided to an image analyzer 110. According to some embodiments, the image analyzer 110 may include various components configured to process / modify the multi-channel image 108 as needed. For example, the image analyzer 110 may include a tone mapping unit 112 (e.g., configured to perform global / local tone mapping operations, inverse tone mapping operations, etc.), a noise reduction unit 114 (e.g., configured to reduce global / local noise in the multi-channel image), a color correction unit 116 (e.g., configured to perform global / local color corrections on the multi-channel image), and a sharpening unit 118 (e.g., configured to perform global / local sharpening corrections on the multi-channel image). It should be noted that the image analyzer 110 is not limited to the aforementioned processing units, and the image analyzer 110 may incorporate any number of processing units configured to perform any processing / modifications on the multi-channel image 108 without departing from the scope of the present disclosure.

[0026] 1, the multi-channel image 108 may be provided to the gain map generator 120 after being processed by the image analyzer 110. However, it should be noted that the multi-channel image 108 may bypass the image analyzer 110 and be provided to the gain map generator 120, if desired, without departing from the scope of this disclosure. It should also be noted that the multi-channel image 108 may bypass one or more of the processing units of the image analyzer 110 without departing from the scope of this disclosure. For example, two given multi-channel images may pass through the tone mapping unit 112 to receive local tone mapping modifications and then bypass the remaining processing units in the image analyzer 110. In this regard, the two multi-channel images that have undergone local tone mapping operations may be utilized to generate a gain map 123 that reflects the local tone mapping operations that have been performed.

[0027] In either case, as described in more detail herein, upon receiving the two multi-channel images 108, the gain map generator 120 can generate a gain map 123 based on the two multi-channel images 108. The gain map generator 120 can then store the gain map 123 in one of the two multi-channel images 108 to generate the enhanced multi-channel image 122. It is further noted that the gain map generation technique can be performed at any time relative to the receipt of the multi-channel image on which the gain map is based. For example, the gain map generator 120 can be configured to postpone generation of the gain map when the digital imaging unit is actively being used to ensure that adequate processing resources are available so that no slowdown is imposed on the user. A more detailed breakdown of how the gain map generator 120 can generate the gain map 123 is provided below in connection with FIGS. 2A-2H, 3A-3F, and 4A-4F.

[0028] Additionally, although not shown in FIG. 1 , one or more compressors may be implemented on the computing device 102 to compress the enhanced multi-channel image 122. For example, the compressor may implement a Lempel-Ziv-Welch (LZW)-based compressor, other types of compressors, a combination of compressors, etc. Furthermore, the compressor may be implemented in any manner to establish the most efficient environment for compressing the enhanced multi-channel image 122. For example, multiple buffers may be instantiated (pixels may be pre-processed in parallel), each buffer may be coupled to a separate compressor, and the buffers may be compressed simultaneously in parallel. Furthermore, compressors of the same or different types may be coupled to each buffer based on the format of the enhanced multi-channel image 122.

[0029] 1 , the image analyzer 110 can be configured to receive and process the enhanced multi-channel image 122 that includes the gain map 123. In particular, the image analyzer 110 can be configured to receive a given enhanced multi-channel image 122 and extract a baseline image from the enhanced multi-channel image 122 and one or more gain maps 123 included therein. The image analyzer 110 can then utilize the baseline image and a particular one of the one or more gain maps 123 to regenerate a version of the baseline image from which the gain map 123 was derived. For example, if the baseline image constitutes an HDR image and the gain map 123 was generated based on the HDR image and an SDR image that is the HDR image's counterpart, the gain map 123 can be applied to the HDR image to regenerate the SDR image (without requiring the SDR image itself to be included in the enhanced multi-channel image 122). It should be noted that the above-described techniques represent only one example of various ways in which the image analyzer 110 can interact with the enhanced multi-channel image 122, and a more detailed breakdown of various alternative techniques is provided below in conjunction with Figures 2A-2H, 3A-3F, and 4A-4F.

[0030] 1 thus provides a high-level overview of different hardware / software architectures that may be implemented by computing device 102 to perform the various techniques described herein. A more detailed breakdown of these techniques is described below in conjunction with FIGS. 2A-2H, 3A-3F, and 4A-4F.

[0031] 2A-2H show a series of conceptual diagrams of a technique for utilizing a gain map to manage edits to different versions of an image, according to some embodiments. As shown in FIG. 2A, step 210 may include the computing device 102 receiving an enhanced multi-channel image 212 comprised of pixels 214. In particular, the pixels 214 include interleaved pixels 216 (each denoted as "P") of the multi-channel HDR image as well as interleaved pixels 218 (each denoted as "P'") of the multi-channel gain map. In this regard, the enhanced multi-channel image 212 includes information of both the multi-channel HDR image and the multi-channel gain map.

[0032] Briefly, it should be noted that the information of the multi-channel HDR image and the multi-channel gain map may be stored in the enhanced multi-channel image 212 using other techniques without departing from the scope of this disclosure. In particular, under another technique, each pixel 214 of the enhanced multi-channel image 212 may incorporate information from both the corresponding pixel 216 of the multi-channel HDR image and the corresponding pixel 218 of the multi-channel gain map. For example, if each pixel 216 of the multi-channel HDR image includes three channels (e.g., red, green, and blue) and each pixel 218 of the multi-channel gain map includes three channels (e.g., red, green, and blue), the corresponding pixel 214 of the enhanced multi-channel image 212 may include six channels (the first three of the six channels store the three channels of pixel 216, and the second three of the six channels store the three channels of pixel 218).

[0033] In another approach, the pixels 216 of the multi-channel HDR image can be stored as primary pixel information of the enhanced multi-channel image 212, and the pixels 218 of the multi-channel gain map can be stored as secondary (e.g., meta-database, attachment-based, image-based, etc.) information of the enhanced multi-channel image 212. Again, these approaches are merely exemplary, and any feasible approach for storing the multi-channel HDR image and the multi-channel gain map within the enhanced multi-channel image 212 can be employed without departing from the scope of this disclosure. Furthermore, it should be noted that the enhanced multi-channel images 212 are not limited to storing HDR images as their baseline images. Conversely, a given enhanced multi-channel image 212 can store any form of image as its baseline image without departing from the scope of this disclosure. For example, the enhanced multi-channel image 212 can instead include a multi-channel SDR image and a multi-channel gain map that enables generating a corresponding multi-channel HDR image (using the multi-channel SDR image and the multi-channel gain map).

[0034] FIG. 2B illustrates step 220, which involves the computing device 102 extracting a multi-channel HDR image (shown as multi-channel HDR image 215 (having pixels 216)) and a multi-channel gain map (shown as multi-channel gain map 217 (having pixels 218)) from the enhanced multi-channel image 212. As shown in FIG. 2B, the pixels 216 of the multi-channel HDR image 215 (and the pixels 218 of the multi-channel gain map 217) may be arranged according to a row / column layout, with the subscripts (e.g., "1,1") of each pixel indicating the pixel's location according to row and column. In the example shown in FIG. 2B, the pixels of the multi-channel HDR image 215 and the multi-channel gain map 217 are arranged in an equal number of rows and columns to form a square image with corresponding / overlapping pixel arrangements. However, it should be noted that the techniques described herein may be applied to multi-channel images with different layouts (e.g., unequal row / column counts). 2B, each pixel (216 / 218) may be comprised of three subpixels: a red subpixel (e.g., designated "R"), a green subpixel (e.g., designated "G"), and a blue subpixel (e.g., designated "B"). However, it should be noted that each pixel (216 / 218) may be comprised of any number of subpixels without departing from the scope of the present disclosure.

[0035] In either case, at the end of step 220, the computing device 102 has placed both the multi-channel HDR image 215 and the multi-channel gain map 217 in memory (e.g., random access memory (RAM)) so that they can be easily accessed and manipulated by the computing device 102.

[0036] 2C illustrates step 230, which involves computing device 102 generating multi-channel SDR image 232 by performing multiplication operation 231 involving multi-channel HDR image 215 and multi-channel gain map 217. Note that the multiplication operations described herein may be performed in linear space or non-linear space (e.g., by performing the calculation in a non-linear gamma-encoded space). An overview of how multi-channel gain map 217 was originally generated (described in more detail below) provides additional context that is helpful in understanding how multi-channel SDR image 232 is generated in FIG. 2C.

[0037] According to some embodiments, the multi-channel gain map 217 was previously generated by comparing the multi-channel HDR image 215 with a previous, pristine multi-channel SDR image, i.e., the SDR counterpart of the multi-channel HDR image 215. For example, the multi-channel SDR image may be generated based on a single-exposure capture of the same scene captured by the multi-channel HDR image 215, such that the multi-channel SDR image and the multi-channel HDR image 215 are substantially related to one another. For example, if the multi-channel HDR image 215 was generated using the EV-, EV0, and EV+ approach described herein, the multi-channel SDR image may be based on the EV0 exposure (e.g., before the EV0 exposure was merged with the EV- and EV+ exposures to generate the multi-channel HDR image 215). This approach can ensure that both the multi-channel HDR image 215 and the multi-channel SDR image correspond to the same scene at the same moment in time. In this way, pixels of the multi-channel HDR image 215 and the multi-channel SDR image may differ only in the luminous intensity collected from the same point in the same scene (as opposed to differing in scene content due to motion resulting from the passage of time through successively captured exposures).

[0038] In either case, according to some embodiments, the multi-channel gain map 217 was generated by dividing the value of each pixel of the previous, pristine multi-channel SDR image by the value of the corresponding pixel of the multi-channel HDR image 215 to generate a quotient. Each quotient can then be assigned to the value of the corresponding pixel 218 in the multi-channel gain map 217. For example, if a given pixel of the multi-channel HDR image 215 had a value of “5” and the corresponding pixel of the previous, pristine multi-channel SDR image had a value of “1,” the quotient was “0.2” and assigned to the value of the corresponding pixel 218 in the multi-channel gain map 217. In this manner, the corresponding pixel of the previous, pristine multi-channel SDR image can be reproduced by multiplying the corresponding pixel 216 of the multi-channel HDR image 215 (which has a value of “5”) by the corresponding pixel 218 of the multi-channel gain map 217 (which has a value of “0.2”), as described in more detail herein. In particular, the multiplication produces a product of "1", which matches the value "1" of the corresponding pixel in the previous pristine multi-channel SDR image.

[0039] Thus, by storing the multi-channel gain map 217 along with the multi-channel HDR image 215, the previous, pristine multi-channel SDR image can be reproduced in Figure 2C (as multi-channel SDR image 232) without the need to store information about the previous, pristine multi-channel SDR image in the enhanced multi-channel image 212. In this regard, at the end of step 230, the multi-channel SDR image 232 can be stored in memory of the computing device 102 to allow for modification and utilization of the multi-channel SDR image 232.

[0040] 2D illustrates step 240, which includes the computing device 102 receiving and applying image modification instructions 242 to the multi-channel HDR image 215. The image modification instructions 242 may represent any possible image modification to the multi-channel HDR image 215. For example, the image modification instructions 242 may include applying a markup to the multi-channel HDR image 215, applying a filter to the multi-channel HDR image 215, applying a photographic style to the multi-channel HDR image 215, applying a destination display device profile to the multi-channel HDR image 215, applying a color correction profile to the multi-channel HDR image 215, etc. It should be noted that the foregoing examples are not intended to be limiting, and the image modification instructions 242 may represent any possible modification that may be made to the multi-channel HDR image 215 without departing from the scope of the present disclosure.

[0041] 2E illustrates step 250, which includes the computing device 102 determining and applying complementary image modification instructions 242 (denoted as image modification instructions 242′) to the multi-channel SDR image 232. According to some embodiments, determining the complementary image modification instructions 242′ may include adjusting the image modification instructions 242 based on differences identified between the multi-channel HDR image 215 and the multi-channel SDR image 232. For example, instructions specific to the higher bit range of the multi-channel HDR image 215 may be adapted according to the lower bit range of the multi-channel SDR image 232. It should be noted that the modification techniques are not limited to the foregoing examples, and that the image modification instructions 242 may be adjusted in any capacity without departing from the scope of this disclosure. It should further be noted that the image modification instructions 242 may be first applied to the multi-channel SDR image 232 (instead of the multi-channel HDR image 215) without departing from the scope of this disclosure. In this alternative, the image modification instructions 242 are adapted to account for differences between the multi-channel HDR image 215 and the multi-channel SDR image 232. This may include, for example, adjusting the image modification instructions 242 to account for the higher bit depth available in the multi-channel HDR image 215.

[0042] In either case, at the end of step 250, image modification instructions 242' (complementary to image modification instructions 242) are applied to multi-channel SDR image 232, so that multi-channel HDR image 215 and multi-channel SDR image 232 have been edited in a similar manner (while taking into account their differences / limitations). This approach provides various benefits, including eliminating the need for a user to manually determine and apply complementary image modification instructions 242', a task that is typically cumbersome and can produce inconsistent results.

[0043] 2F illustrates step 260, which involves the computing device 102 generating a multi-channel gain map 262 (composed of pixels 233) by performing a comparison 261 between the multi-channel HDR image 215 (modified in FIG. 2D) and the multi-channel SDR image 232 (modified in FIG. 2E). Here, if it is desired to enable the multi-channel SDR image 232 to be reproduced using the multi-channel HDR image 215, a first approach may be utilized. In particular, the first approach involves dividing the value of each pixel of the multi-channel SDR image 232 by the value of the corresponding pixel of the multi-channel HDR image 215 to generate a quotient. Each quotient can then be assigned to the value of the corresponding pixel 263 in the multi-channel gain map 262. For example, the "P" of the multi-channel HDR image 215 may be 1,1 ” has a value of “4”, and the pixel indicated by “P 1,1 If the pixel indicated by "P" has a value of "2", the quotient will be "0.5" and the "P" in the multi-channel gain map 262 1,1 In this manner, and as will be explained in more detail herein, the "P" of the multi-channel SDR image 232 is assigned a value of 1,1 The pixels indicated by "P" in the multi-channel HDR image 215 1,1 ” in the multi-channel gain map 262 (having a value of “4”). 1,1 In particular, the multiplication is performed by multiplying the pixel indicated by "P" (which has a value of "0.5") in the multi-channel SDR image 232. 1,1 2G. Storing the multi-channel gain map 262 with the multi-channel HDR image 215 can therefore allow the multi-channel SDR image 232 to be reproduced independently of the multi-channel SDR image 232 itself. A more detailed description of various ways in which the multi-channel gain map 262 may be stored with the corresponding multi-channel image is described below in connection with FIG. 2G.

[0044] Alternatively, if it is desired to enable the multi-channel HDR image 215 to be reproduced using the multi-channel SDR image 232, a second (different) approach may be utilized. In particular, the second approach involves dividing the value of each pixel of the multi-channel HDR image 215 by the value of the corresponding pixel of the multi-channel SDR image 232 to generate a quotient. Each quotient can then be assigned to the value of the corresponding pixel 263 in the multi-channel gain map 262. For example, 1,1 ” has a value of “2”, and the pixel indicated by “P 1,1 If the pixel indicated by "P" has a value of "8", the quotient will be "4" and the "P" in the multi-channel gain map 262 1,1 In this way, and as will be explained in more detail herein, the value of the pixel indicated by "P" in the multi-channel HDR image 215 is assigned. 1,1 The pixels denoted by "P" are the pixels of the multi-channel SDR image 232. 1,1 ” in the multi-channel gain map 262. 1,1 In particular, the multiplication is performed by multiplying the pixel indicated by "P" (which has a value of "4") in the multi-channel HDR image 215. 1,1 2G. Storing the multi-channel gain map 262 with the multi-channel SDR image 232 can therefore allow the multi-channel HDR image 215 to be reproduced independently of the multi-channel HDR image 215 itself. Again, a more detailed description of various ways in which the multi-channel gain map 262 may be stored with the corresponding multi-channel image is described below in connection with FIG. 2G.

[0045] 2F (and described herein) constitutes a pixel-level comparison, but embodiments are not so limited. Conversely, pixels of images may be compared to one another at any level of granularity without departing from the scope of this disclosure. For example, sub-pixels of multi-channel HDR image 215 and multi-channel SDR image 232 may be compared to one another (instead of, or in addition to, pixel-level comparison) such that multiple gain maps are generated under different comparison techniques (e.g., separate gain maps for each color channel).

[0046] Additionally, it should be noted that various optimizations may be employed when generating the gain map without departing from the scope of the present disclosure. For example, if two values ​​are identical to each other, a comparison operation may be skipped, and a single-bit value (e.g., “0”) may be assigned to the corresponding value in the gain map to minimize the size (i.e., storage requirements) of the gain map. Furthermore, the resolution of the gain map may be smaller than the resolution of the images being compared to generate the gain map. For example, an approximation of every fourth pixel in a first image may be compared with a corresponding approximation of every fourth pixel in a second image to generate a gain map that is one-quarter the resolution of the first and second images. This approach substantially reduces the size of the gain map, but reduces the overall accuracy with which the first image can be reproduced from the second image and gain map (or vice versa). Furthermore, the first and second images may be resampled in any conceivable manner before generating the gain map. For example, the first and second images may undergo a local tone mapping operation before generating the gain map.

[0047] 2G illustrates a step 270 in which the computing device 102 embeds a multi-channel gain map 262 into the multi-channel HDR image 215 or the multi-channel SDR image 232, according to some embodiments. In particular, when the first technique described above in connection with FIG. 2F is utilized, which enables the multi-channel HDR image 215 and the multi-channel gain map 262 to be used to reproduce the multi-channel SDR image 232, the computing device 102 embeds the multi-channel gain map 262 into the multi-channel HDR image 215 (thereby generating the enhanced multi-channel image 122). As shown in FIG. 2G, one technique for embedding the multi-channel gain map 262 into the multi-channel HDR image 215 includes interleaving each pixel 263 (of the multi-channel gain map 262) with its corresponding pixel 216 (of the multi-channel HDR image 215). An alternative approach may include embedding each pixel 263 (of the multi-channel gain map 262) into its corresponding pixel 216 (of the multi-channel HDR image 215) as an additional channel of the pixel 216. Yet another approach may include embedding the multi-channel gain map 262 as metadata stored with the multi-channel HDR image 215. It should be noted that the aforementioned approaches are exemplary and not intended to be limiting, and that the multi-channel gain map 262 (as well as other supplemental gain maps, if generated) may be stored with the multi-channel HDR image 215 using any conceivable approach without departing from the scope of the present disclosure. Furthermore, it should be noted that a similar (i.e., complementary) procedure may be applied when the second approach described above in connection with 2F is utilized, which allows the multi-channel SDR image 232 and the multi-channel gain map 262 to be used to reproduce the multi-channel HDR image 215.

[0048] 2H illustrates a method 280 for managing edits to different versions of an image using a gain map, according to some embodiments. As shown in FIG. 2H, method 280 begins at step 282, where computing device 102 accesses an enhanced image including a high dynamic range (HDR) image and a gain map (e.g., as described above in connection with FIG. 2A). In step 284, computing device 102 extracts the HDR image and gain map from the enhanced image (e.g., as described above in connection with FIG. 2B). In step 286, computing device 102 generates a standard dynamic range (SDR) image using the HDR image and gain map (e.g., as described above in connection with FIG. 2C).

[0049] In step 288, the computing device 102 receives and applies first modification instructions to the HDR image (e.g., as described above in conjunction with FIG. 2D). In step 290, the computing device 102 generates second modification instructions based on at least the first modification instructions (e.g., as described above in conjunction with FIG. 2E). In step 292, the computing device 102 applies the second modification instructions to the SDR image (e.g., as described above in conjunction with FIG. 2E). In step 294, the computing device 102 generates a second gain map by comparing the HDR image with the SDR image (e.g., as described above in conjunction with FIG. 2F), or vice versa. In step 296, the computing device 102 embeds the second gain map into the HDR image or the SDR image (e.g., as described above in conjunction with FIG. 2G).

[0050] Further, it should be noted that under an alternative approach, when the computing device 102 determines that the image modification instructions 242 applied to the multi-channel HDR image 215 can be modified to apply to the multi-channel gain map 217, the generation of the multi-channel SDR image 232 (described above in connection with FIG. 2C ) can be omitted. In particular, the multi-channel gain map 217 can be modified to generate a modified multi-channel gain map 217 that, when applied to the multi-channel HDR image 215, generates the multi-channel SDR image 232 as if the multi-channel SDR image 232 had been modified using the technique described above in connection with step 250 of FIG. 2E . This approach can improve the overall efficiency with which the computing device 102 implements the image modification instructions in that redundant modifications to the multi-channel SDR image 232, as well as subsequent gain map regeneration operations, can be eliminated.

[0051] 3A-3F are a series of conceptual diagrams of a technique for utilizing a gain map to manage the output of an image on a display device, according to some embodiments. As shown in FIG. 3A, step 310 may include the computing device 102 receiving an enhanced multi-channel image 312 comprised of pixels 314. In particular, similar to the scenario described above in connection with FIG. 2A, the pixels 314 include interleaved pixels 316 (each denoted "P") of the first version of the multi-channel image and interleaved pixels 318 (each denoted "P'") of the multi-channel gain map. In this regard, the enhanced multi-channel image 312 includes information from both the first version of the multi-channel image and the multi-channel gain map. Again, it should be noted that the embedding technique shown in FIG. 3A is not intended to be limiting, and any conceivable technique may be used to incorporate information from the first version of the multi-channel image and the multi-channel gain map into the enhanced multi-channel image 312 without departing from the scope of this disclosure.

[0052] 3B illustrates step 320, which involves the computing device 102 extracting from the enhanced multi-channel image 312 a first version of the multi-channel image (shown as multi-channel image 315) and a multi-channel gain map (shown as multi-channel gain map 317). This extraction can be performed using the same or similar techniques as described above in connection with FIG. 2B. In either case, at the end of step 320, the computing device 102 has placed both the multi-channel image 315 and the multi-channel gain map 317 in memory (e.g., random access memory (RAM)) so that they can be easily accessed and manipulated by the computing device 102.

[0053] 3C illustrates step 330, which includes computing device 102 identifying a headroom level 334 for a second version of the image based on a current brightness setting 333 of a display device 332 (communicatively coupled to computing device 102). According to some embodiments, the current brightness setting 333 of display device 332 can affect the dynamic range of color / luminosity that the display device 332 can accurately display for human perception. In particular, as the brightness setting of the display device increases, the dynamic range of color / luminosity that can be accurately output by the display device 332 shrinks, while as the brightness setting of the display device decreases, the dynamic range of color / luminosity that can be accurately output by the display device 332 increases. In this regard, it may be beneficial to scale the color / luminosity range of a given image, which may be performed using the aforementioned headroom level 334 according to the current brightness of the display device. This approach provides various benefits in that the display device is not constrained to display images having colors / luminosity that are outside the current range that the display device is capable of displaying.

[0054] Additional factors may be considered when generating the headroom level 334 without departing from the scope of the present disclosure. For example, the headroom level 334 may be based on environmental factors such as the current external lighting conditions relative to the display device 332 (e.g., detectable using one or more light sensors) (which, like the current brightness setting 333 of the display device 332, may affect the color / luminosity output by the display device 332 and accurately perceived by humans). In another example, the headroom level 334 may be based on wear level information associated with the display device 332. For example, the wear level information (i.e., a pixel-level usage map) may indicate that certain pixels of the display device 332 are moved more frequently relative to other pixels of the display device 332, thereby preventing them from accurately displaying color / luminosity. The foregoing examples are not intended to be limiting, and it should be noted that any information affecting the ability of the display device 332 to accurately display color / luminosity may be used to establish the headroom level 334 at any level of granularity without departing from the scope of the present disclosure.

[0055] According to some embodiments, the headroom level 334 represents a single value (e.g., a weight) that is applied to the multi-channel gain map 317 before utilizing the multi-channel gain map 317 to generate a second version of the multi-channel image (as described in more detail below in conjunction with FIG. 3D ). Under another approach, the headroom level 334 can take the form of a collection of weights that are correspondingly applied to the multi-channel gain map 317. This approach can include, for example, a separate weight for each pixel in the enhanced multi-channel image 312 (1:1 ratio), a separate weight for every two pixels in the enhanced multi-channel image 312 (1:2 ratio), or a separate weight for every N pixels in the enhanced multi-channel image 312 (1:N ratio). Again, it should be noted that the foregoing examples are not meant to be limiting, and the headroom level 334 can take any form that modifies the multi-channel gain map 317 at any level of granularity without departing from the scope of this disclosure.

[0056] In either case, as shown in Figure 3C, step 330 includes computing device 102 establishing a modified multi-channel gain map 336 (including pixel 337) based on headroom level 334. As shown in Figure 3C, pixel 337 of multi-channel gain map 317 is denoted by "P" to indicate that it has been modified relative to pixel 318 of multi-channel gain map 336, which is denoted by "P'".

[0057] 3D illustrates step 340, in which the computing device 102 generates a second version of the multi-channel image by performing a multiplication operation 341 involving the first version of the multi-channel image (i.e., multi-channel image 315) and a modified multi-channel gain map 336. As illustrated in FIG. 3D, the above-described generation of the modified multi-channel gain map 336 can be performed using techniques similar to those described above in connection with FIG. 2C. In either case, the generation results in a second version of the multi-channel image (illustrated in FIG. 3D as multi-channel image 342 (including pixel 343)) that can be output on a display device 332. Accordingly, FIG. 3E illustrates step 350, in which the computing device 102 causes the second version of the multi-channel image (i.e., multi-channel image 342) to be displayed on the display device 332. In this regard, multi-channel image 342 represents a modified version of multi-channel image 315 optimized for display on the display device 332 based on the headroom level 334 described above in connection with FIG. 3C.

[0058] Additionally, FIG. 3F illustrates a method 360 for utilizing a gain map to manage the output of an image on a display device, according to some embodiments. As shown in FIG. 3F, method 360 begins at step 362, where computing device 102 accesses an enhanced image including a first version of the image and multiple gain maps. In step 362, computing device 102 identifies a headroom level for a second version of the image based on the current brightness setting of the display device (e.g., as described above with respect to FIG. 3C). In step 364, computing device 102 identifies a particular gain map from the multiple gain maps that corresponds to the headroom level. In step 366, computing device 102 generates a second version of the image using the first version of the image and the particular gain map. In step 368, computing device 102 causes the second version of the image to be displayed on the display device (e.g., as described above with respect to FIG. 3E).

[0059] It should further be noted that the enhanced multi-channel image can include multiple gain maps spanning the range of brightness that can be shown by the display device. For example, if a given display device is capable of displaying 20 different brightness levels, the enhanced multi-channel image can include 20 different gain maps, each corresponding to a different one of the 20 different brightness levels. In this regard, the gain map modification operation described above in connection with FIGS. 3A-3F can be replaced with a simple lookup (and application) of the appropriate gain map corresponding to the current brightness level. This approach can increase the overall speed at which the baseline multi-channel image in the enhanced multi-channel image can be adjusted for output on the display device at its current brightness level. It should further be noted that the multiple gain maps can be based on other display factors described herein, including external lighting conditions relative to the display. This can include, for example, identifying an appropriate gain map based on the current brightness level of the display and then modifying the appropriate gain map based on the external lighting conditions relative to the display (or vice versa). It should be noted that the foregoing approach is not meant to be limiting, and without departing from the scope of this disclosure, the enhanced multi-channel image may include any number of gain maps based on any number of factors affecting display output capabilities.

[0060] 4A-4F are a series of conceptual diagrams for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. As shown in FIG. 4A, step 410 includes computing device 102 accessing a multi-channel HDR image 411 (including pixels 412 and sub-pixels 414, as described herein). This may include, for example, computing device 102 receiving a request to import the multi-channel HDR image 411 into a photo library managed by computing device 102 and accessible to a user of computing device 102. This may occur, for example, when a user is importing an HDR image from an advanced digital camera (with HDR capabilities), when a user is receiving an HDR image from another person, etc. Under these scenarios, it may be desirable to be able to accurately display an SDR version of the HDR image when appropriate, especially if a display device communicatively coupled to computing device 102 is capable of displaying only the color / luminosity of an SDR image. This may also be desirable when an HDR image and an SDR image are displayed between each other as thumbnail images, because a user typically sees the HDR image as being too bright for the SDR image (even when displayed properly on an HDR-enabled display). In this scenario, the computing device 102 utilizes a gain map to reduce (partially or fully) the HDR image to a range that matches the SDR image (and / or vice versa) in order to balance the overall intensity of the thumbnail.

[0061] 4B thus illustrates step 420, in which the computing device 102 generates a multi-channel SDR image 422 (including pixel 423) by applying a global tone mapping operation 421 to the multi-channel HDR image 411. Here, generation is necessary if the multi-channel HDR image 411, unlike the enhanced multi-channel image described herein, does not (yet) include a multi-channel gain map that enables a corresponding multi-channel SDR image to be generated. However, as described herein, the global tone mapping operation 421 may be utilized to generate an approximation of the corresponding multi-channel SDR image. In particular, the global tone mapping operation may include mapping an expanded HDR color gamut to a more limited SDR color gamut, with an effort to reduce the introduction of artifacts (such as banding due to reduced bit depth, which reduces the granularity with which gradient transitions can appear). Note that any alternative (or additional) image-based processing / modification may be applied to the multi-channel HDR image 411 without departing from the scope of this disclosure.

[0062] In either case, Figure 4C illustrates step 430, which involves computing device 102 generating multi-channel gain map 434 (including pixel 435) by performing a comparison 432 between multi-channel HDR image 411 and multi-channel SDR image 422. The same or similar techniques as described above in connection with Figure 2F can be utilized to perform comparison 432 (particularly the first approach, which involves dividing the value of each pixel of multi-channel SDR image 422 by the value of the corresponding pixel of multi-channel HDR image 411 to generate a quotient).

[0063] Next, FIG. 4D illustrates step 440, which includes the computing device 102 embedding the multi-channel gain map 434 into the multi-channel HDR image 411. Using the same or similar techniques described above in connection with FIG. 2G, step 440 can be performed, which includes injecting information about pixel 435 of the multi-channel gain map 434 into the multi-channel HDR image 411 (e.g., as neighboring pixel information, extended channel information, additional metadata information, separate image information, etc.), as shown in FIG. 4D. At this point, the multi-channel HDR image 411 effectively transitions to the enhanced multi-channel image 122, which includes the multi-channel HDR image 411 and the multi-channel gain map 434. Additionally, the multi-channel HDR image 411 and the multi-channel gain map 434 can be used to reconstruct the multi-channel SDR image 422, eliminating the need to retain the multi-channel SDR image 422. Accordingly, FIG. 4E illustrates step 450, which includes the computing device 102 discarding the multi-channel SDR image 422.

[0064] 4F illustrates a method 460 for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map, according to some embodiments. As shown in FIG. 4F, method 460 begins at step 462, where computing device 102 accesses a high dynamic range (HDR) image (e.g., as described above in connection with FIG. 4A). In step 464, computing device 102 generates a standard dynamic range (SDR) image by applying a global tone mapping operation to the HDR image (e.g., as described above in conjunction with FIG. 4B).

[0065] At step 466, computing device 102 generates a gain map by comparing the SDR image with the HDR image (e.g., as described above in connection with FIG. 4C). At step 468, computing device 102 embeds the gain map into the HDR image (e.g., as described above in connection with FIG. 4D). At step 470, computing device 102 receives a request to view an SDR version of the HDR image. At step 472, computing device 102 provides an SDR version of the HDR image using the HDR image and the gain map.

[0066] FIG. 5 illustrates a detailed diagram of a computing device 500 that can be used to perform various techniques described herein, according to some embodiments. In particular, the detailed diagram illustrates various components that may be included in the computing device 102 described in connection with FIG. 1. As shown in FIG. 5, the computing device 500 may include a processor 502, which represents a microprocessor or controller for controlling the overall operation of the computing device 500. The computing device 500 may also include a user input device 508 that allows a user of the computing device 500 to interact with the computing device 500. For example, the user input device 508 may take various forms, such as input in the form of buttons, keypads, dials, a touchscreen, an audio input interface, a visual / image capture input interface, sensor data, etc. Additionally, the computing device 500 may include a display 510 that may be controlled by the processor 502 (e.g., via a graphics component) to display information to the user. A data bus 516 may facilitate data transfer between at least the storage device 540, the processor 502, and the controller 513. The controller 513 may be used to interface with and control different devices through an device control bus 514. The computing device 500 may also include a network / bus interface 511 that couples to a data link 512. In the case of a wireless connection, the network / bus interface 511 may include a wireless transceiver.

[0067] As mentioned above, the computing device 500 also includes a storage device 540, which may include a single disk or a collection of disks (e.g., a hard drive). In some embodiments, the storage device 540 may include flash memory, semiconductor (solid-state) memory, or the like. The computing device 500 may also include a random access memory (RAM) 520 and a read-only memory (ROM) 522. The ROM 522 may store executed programs, utilities, or processes in a non-volatile manner. The RAM 520 may provide volatile data storage and stores instructions related to the operation of applications executing on the computing device 500, for example, the image analyzer 110 / gain map generator 120.

[0068]

[0006] Techniques described herein include a first technique for utilizing a gain map to manage edits to different versions of an image. According to some embodiments, the first technique can be implemented by a computing device and includes: (1) accessing an enhanced image including a high dynamic range (HDR) image and a gain map; (2) extracting the HDR image and the gain map from the enhanced image; (3) generating a standard dynamic range (SDR) image using the HDR image and the gain map; (4) receiving and applying first modification instructions to the HDR image; (5) generating second modification instructions based on at least the first modification instructions; (6) applying the second modification instructions to the SDR image; (7) generating a second gain map by comparing the HDR image to the SDR image, or vice versa; and (8) embedding the second gain map into the HDR image or the SDR image.

[0069] According to some embodiments, generating the second modification instructions based on at least the first modification instructions includes (1) identifying at least one modification to the HDR image caused by applying the first modification instructions, and (2) determining how to apply at least one complementary modification to the SDR image, wherein the second modification instructions, when applied to the SDR image, cause at least one complementary modification to the SDR image.

[0070] According to some embodiments, the first technique may further include, before accessing the HDR image, (1) receiving at least a first exposure of a scene and a second exposure of the scene, the first and second exposures being captured at a bit depth for storing the HDR image, and (2) processing the first and second exposures to generate the HDR image.

[0071] According to some embodiments, comparing the HDR image with the SDR image includes, for each pixel of the HDR image, (i) identifying a corresponding pixel in the SDR image, (ii) dividing the pixel by the corresponding pixel to generate a quotient, and (iii) storing the quotient as the corresponding pixel in a second gain map. According to some embodiments, the second gain map is embedded in the SDR image. According to some embodiments, comparing the SDR image with the HDR image includes, for each pixel of the SDR image, (i) identifying a corresponding pixel in the HDR image, (ii) dividing the pixel by the corresponding pixel to generate a quotient, and (iii) storing the quotient as the corresponding pixel in the second gain map. According to some embodiments, the second gain map is embedded in the HDR image.

[0072] Techniques described herein include a second technique for utilizing multiple gain maps to manage the output of an image on a display device. According to some embodiments, the second technique may be implemented by a computing device and includes: (1) accessing an enhanced image including a first version of the image and multiple gain maps, (2) identifying a headroom level for the second version of the image based on a current brightness setting of the display device, (3) identifying a particular gain map from the multiple gain maps that corresponds to the headroom level, (4) generating the second version of the image using the first version of the image and the particular gain map, and (5) displaying the second version of the image on the display device.

[0073] According to some embodiments, the headroom level is further based on the color gamut capacity of the display device and / or external lighting conditions relative to the display device. According to some embodiments, the external lighting conditions are detected using at least one light sensor communicatively coupled to the computing device. According to some embodiments, the headroom level scales inversely with the current brightness setting. According to some embodiments, the second version of the image is output accurately according to the brightness setting of the display device. According to some embodiments, the first version of the image includes a standard dynamic range (SDR) version of the scene, and the second version of the image includes a high dynamic range (HDR) version of the scene. According to some embodiments, the HDR version of the scene is generated based on first, second, and third exposures of the scene, and the SDR version of the scene is generated based on the second exposure of the scene.

[0074] The techniques described herein include a third technique for generating a gain map that enables generating a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and a gain map. According to some embodiments, the third technique can be implemented by a computing device and includes: (1) accessing an HDR image; (2) generating an SDR image by applying a global tone mapping operation to the HDR image; (3) generating a gain map by comparing the SDR image with the HDR image; (4) embedding the gain map in the HDR image; (5) receiving a request to view an SDR version of the HDR image; and (6) utilizing the HDR image and the gain map to provide an SDR version of the HDR image.

[0075] According to some embodiments, the global tone mapping operation reduces the bit depth of each pixel included in the HDR image. According to some embodiments, comparing the SDR image to the HDR image includes, for each pixel of the SDR image, (i) identifying a corresponding pixel in the HDR image, (ii) dividing the pixel by the corresponding pixel to generate a quotient, and (iii) storing the quotient as the corresponding pixel in a gain map. According to some embodiments, embedding the gain map in the HDR image includes, for each pixel of the gain map, (i) identifying a corresponding pixel in the HDR image, and (ii) storing the pixel's value as supplemental information to the corresponding pixel. According to some embodiments, embedding the gain map in the HDR image includes storing the gain map as metadata associated with the HDR image.

[0076] According to some embodiments, utilizing the HDR image and the gain map to provide an SDR version of the HDR image includes, for each pixel of the gain map, multiplying the pixel by a corresponding pixel in the HDR image to generate a corresponding pixel of the SDR version of the HDR image.

[0077] Various aspects, embodiments, implementations, or features of the described embodiments can be used individually or in any combination. Various aspects of the described embodiments can be implemented by software, hardware, or a combination of hardware and software. The described embodiments can also be embodied as computer-readable code on a computer-readable medium. The computer-readable medium is any data storage device that can store data which can thereafter be read by a computer system. Examples of computer-readable media include read-only memory, random-access memory, CD-ROMs, DVDs, magnetic tape, hard disk drives, solid-state drives, and optical data storage devices. The computer-readable medium can also be distributed over network-coupled computer systems so that the computer-readable code is stored and executed in a distributed fashion.

[0078] In the foregoing description, for purposes of explanation, specific terminology was used to provide a thorough understanding of the described embodiments. However, it will be apparent to those skilled in the art that specific details are not required to practice the described embodiments. Thus, the descriptions of the specific embodiments set forth above are presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the described embodiments to the precise forms disclosed. It will be apparent to those skilled in the art that numerous modifications and variations are possible in light of the above teachings.

Claims

1. 1. A method for utilizing a gain map to manage edits to different versions of an image, the method comprising: accessing an enhanced image comprising a high dynamic range (HDR) image and the gain map; extracting the HDR image and the gain map from the enhanced image; generating a standard dynamic range (SDR) image using the HDR image and the gain map; receiving and applying first modification instructions to the HDR image; generating second modification instructions based on at least the first modification instructions; applying the second modification instructions to the SDR image; generating a second gain map by comparing the HDR image to the SDR image, or vice versa; Embedding the second gain map into the HDR image or the SDR image; A method comprising:

2. 1. A non-transitory computer-readable storage medium configured to store instructions that, when executed by at least one processor included in a computing device, cause the computing device to: accessing an enhanced image comprising a high dynamic range (HDR) image and the gain map; extracting the HDR image and the gain map from the enhanced image; generating a standard dynamic range (SDR) image using the HDR image and the gain map; receiving and applying first modification instructions to the HDR image; generating second modification instructions based on at least the first modification instructions; applying the second modification instructions to the SDR image; generating a second gain map by comparing the HDR image to the SDR image, or vice versa; and embedding the second gain map into the HDR image or the SDR image, thereby utilizing a gain map to manage edits to different versions of an image.

3. 1. A computing device configured to manage edits to different versions of an image utilizing a gain map, the computing device comprising: at least one processor; at least one memory that stores instructions that, when executed by the at least one processor, cause the computing device to: accessing an enhanced image comprising a high dynamic range (HDR) image and the gain map; extracting the HDR image and the gain map from the enhanced image; generating a standard dynamic range (SDR) image using the HDR image and the gain map; receiving and applying first modification instructions to the HDR image; generating second modification instructions based on at least the first modification instructions; applying the second modification instructions to the SDR image; generating a second gain map by comparing the HDR image to the SDR image, or vice versa; and embedding the second gain map into the HDR image or the SDR image.

4. 1. A computing device configured to manage edits to different versions of an image utilizing a gain map, the computing device comprising: means for accessing an enhanced image comprising a high dynamic range (HDR) image and said gain map; means for extracting the HDR image and the gain map from the enhanced image; means for generating a standard dynamic range (SDR) image using the HDR image and the gain map; means for receiving and applying a first modification instruction to the HDR image; means for generating second modification instructions based on at least the first modification instructions; means for applying the second modification instructions to the SDR image; means for generating a second gain map by comparing the HDR image to the SDR image, or vice versa; means for embedding the second gain map into the HDR image or the SDR image; A computing device comprising:

Images