Techniques for managing changing states of images with gain mapping

Abstract

Various techniques for utilizing gain mapping are disclosed. According to some embodiments, a technique for utilizing gain mapping includes: (1) accessing an enhanced image including a high dynamic range (HDR) image and the gain mapping; (2) extracting the HDR image and the gain mapping from the enhanced image; (3) generating a standard dynamic range (SDR) image using the HDR image and the gain map; (4) receiving a first modification instruction and applying the first modification instruction to the HDR image; (5) generating a second modification instruction at least based on the first modification instruction; (6) applying the second modification instruction to the SDR image; (7) generating a second gain map by comparing the HDR image with 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 set forth techniques for managing the varying states of an image using a gain map. In particular, the gain map can be used to provide various features, including generating a second version of an image by utilizing a first version of the image and the gain map. Background Art

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

[0003] Despite the foregoing image sensor limitations, improvements in photographic techniques have enabled the capture of a wider range of light (referred to herein as high dynamic range (HDR)). This can be achieved by: (1) capturing multiple "bracketed portions" of an image, i.e., images with different exposure times (also referred to as "apertures"), and subsequently (2) fusing the bracketed images into a single image that combines different aspects of the different exposures. In this regard, a single HDR image has a wider brightness dynamic range compared to the images that can be captured in each of the individual exposures. This makes HDR images superior to SDR images in several respects.

[0004] Due to advancements in design and manufacturing techniques, display devices capable of displaying HDR images (in their true form) have become more readily available. However, most of the display devices currently in use (and that continue to be manufactured) are only capable of displaying SDR images. Thus, a device with an SDR - limited display that receives an HDR image must perform various tasks to convert (i.e., degrade) the HDR image into 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., upscale) the SDR image into an HDR - image equivalent.

[0005] Unfortunately, the foregoing conversion techniques typically produce inconsistent and / or undesirable results. In particular, degrading an HDR image to an SDR image can introduce visual artifacts (e.g., banding) into the resulting image, which are generally not correctable by additional image processing. Conversely, upscaling an SDR image to an HDR image involves applying varying levels of guesswork, which can also introduce visual artifacts that cannot be corrected.

[0006] Accordingly, what is needed are techniques for enabling an image to transition effectively and accurately between different states. For example, it is desirable to be able to degrade an HDR image to its true SDR counterpart (and vice versa) without relying on the aforementioned (and flawed) conversion techniques. SUMMARY OF THE INVENTION

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

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

[0009] Another embodiment sets forth a method for managing the output of an image on a display device using a gain map. The method includes the steps of: (1) accessing an enhanced image including a first version of the image and the 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) using the first version of the image and the modified gain map to generate the second version of the image, and (5) causing the second version of the image to be displayed on the display device.

[0010] Another implementation describes a method for generating a gain map according to some implementations, which enables the generation of a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and the gain map. The method includes the following steps: (1) accessing the HDR image; (2) generating the SDR image by applying a global tone mapping operation to the HDR image; (3) generating the gain map by comparing the SDR image with the HDR image; (4) embedding the gain map into the HDR image; (5) receiving a request to view the SDR version of the HDR image; and (6) providing the SDR version of the HDR image using the HDR image and the gain map.

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

[0012] In the following detailed description, taken in conjunction with the drawings that illustrate by way of example the principles of the implementations, other aspects and advantages of the present invention will become apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] The present disclosure will be more readily understood by reference to the following detailed description in conjunction with the drawings, in which like reference numerals refer to like structural elements.

[0014] Figure 1 An overview of a computing device configured to perform various techniques described herein according to some implementations is shown.

[0015] Figures 2A to 2H A series of conceptual diagrams illustrating techniques for managing edits to different versions of an image using a gain map according to some implementations is shown.

[0016] Figures 3A to 3F A series of conceptual diagrams illustrating techniques for managing the output of an image on a display device using a gain map according to some implementations is shown.

[0017] Figures 4A to 4F A series of conceptual diagrams illustrating the generation of a gain map that enables the generation of a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and the gain map according to some implementations is shown.

[0018] Figure 5 A detailed view of a computing device that can be used to implement various techniques described herein according to some implementations is shown. DETAILED DESCRIPTION

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

[0020] In the following detailed description, reference is made to the accompanying drawings that form a part of the specification, and specific embodiments in accordance with the described embodiments are illustrated in the drawings. Although these embodiments have been described in sufficient detail to enable those skilled in the art to practice the described embodiments, it should be understood that these examples are not restrictive, and thus other embodiments may be used and changes may be made without departing from the spirit and scope of the described embodiments.

[0021] The representative embodiments set forth herein disclose techniques for managing the changing state of an image using a gain map. In particular, the gain map can be used to provide various features, including generating a second version of an image by utilizing a first version of the image and the gain map. The following is described in conjunction with Figure 1 , Figures 2A to 2H , Figures 3A to 3F , Figures 4A to 4F and Figure 5 to provide a more detailed description of these techniques.

[0022] Figure 1 FIG. 100 shows an overview of a computing device 102 that can be configured to perform the various techniques described herein. As Figure 1 shown, the computing device 102 can include a processor 104, a volatile memory 106, and a non-volatile memory 124. It should be noted that Figure 5 FIG. shows a more detailed breakdown of the exemplary hardware components that can be included in the computing device 102, and these components are omitted from the illustration of Figure 1 for simplicity purposes only. For example, the computing device 102 can include additional non-volatile memories (e.g., solid state drives, hard disk drives, etc.), other processors (e.g., multi-core central processing units (CPUs)), graphics processing units (GPUs), etc. According to some embodiments, an operating system (OS) ( Figure 1(not shown in the figure) can be loaded into the volatile memory 106, where the OS can execute various application programs that together enable the implementation of the various techniques described herein. For example, these application programs can include an image analyzer 110 (and its internal components), a gain map generator 120 (and its internal components), one or more compressors ( Figure 1 (not shown in the figure), etc.

[0023] As Figure 1 shown, 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 ( Figure 1 (not shown in the figure) configured to capture and process digital images. According to some embodiments, the multi-channel image 108 can consist of a set of pixels, where each pixel in the set of pixels includes a set of sub-pixels (e.g., red sub-pixels, green sub-pixels, blue sub-pixels, etc.). It should be noted that the term "sub-pixel" used here can be synonymous with the term "channel". It should also be noted that without departing from the scope of the present disclosure, the multi-channel image 108 can have different resolutions, layouts, bit depths, etc.

[0024] According to some embodiments, a given multi-channel image 108 can represent a standard dynamic range (SDR) image, which constitutes 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, which constitutes multiple exposures of a scene collected and processed by the digital imaging unit. To generate an HDR image, the digital imaging unit can capture the scene at different exposure brackets (e.g., three exposure brackets commonly referred to as "EV0", "EV-", and "EV+"). Generally, the EV0 image corresponds to the normal / ideal exposure of the scene (typically captured using the automatic exposure settings of the digital imaging unit); the EV- image corresponds to an underexposed image of the scene (e.g., four times darker than EV0), and the 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 produce a resulting image that combines a greater range of brightness relative to the SDR image. It should be noted that the multi-channel image 108 discussed herein is not limited to SDR / HDR images. Instead, the multi-channel image 108 can represent any form of digital image (e.g., scanned image, computer-generated image, etc.) without departing from the scope of the present disclosure.

[0025] As Figure 1As shown, the multi-channel image 108 may be (optionally) provided to the 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 correction in the multi-channel image), and a sharpening unit 118 (e.g., configured to perform global / local sharpening correction in the multi-channel image). It should be noted that the image analyzer 110 is not limited to the foregoing processing units, and the image analyzer 110 may incorporate any number of processing units configured to perform any processing / modification on the multi-channel image 108 without departing from the scope of the present disclosure.

[0026] As Figure 1 shown, after being processed by the image analyzer 110, the multi-channel image 108 may be provided to the gain map generator 120. However, it should be noted that, without departing from the scope of the present disclosure, if desired, the multi-channel image 108 may bypass the image analyzer 110 and be provided to the gain map generator 120. 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 the present disclosure. For example, two given multi-channel images may pass through the tone mapping unit 112 to receive local tone mapping modification and then bypass the remaining processing units in the image analyzer 110. In this regard, two multi-channel images (which have undergone local tone mapping operations) may be used to generate a gain map 123 reflecting the local tone mapping operations performed.

[0027] In any case, and as described in more detail herein, the gain map generator 120 may generate a gain map 123 based on two multi-channel images 108 when receiving the two multi-channel images 108. Subsequently, the gain map generator 120 may store the gain map 123 in one of the two multi-channel images 108 to produce an enhanced multi-channel image 122. It should also be noted that the gain map generation technique may be performed at any time relative to the multi-channel image on which the received gain map will be based. For example, the gain map generator 120 may be configured to defer the generation of the gain map when the digital imaging unit is in active use to ensure that sufficient processing resources are available so that no slowdown is imposed on the user. The following is combined with Figures 2A to 2H , Figures 3A to 3F and Figures 4A to 4F provides a more detailed breakdown diagram of the manner in which the gain map generator 120 may generate the gain map 123.

[0028] Additionally, and although not shown in Figure 1 , one or more compressors may be implemented on computing device 102 for compressing the enhanced multi-channel image 122. For example, the compressor may implement a Lempel–Ziv–Welch (LZW)-based compressor, other types of compressors, combinations of compressors, etc. Additionally, the compressor may be implemented in any way to establish the most efficient environment for compressing the enhanced multi-channel image 122. For example, multiple buffers (where pixels may be preprocessed in parallel) may be instantiated, and each buffer may be connected to a corresponding compressor such that the buffers may also be compressed in parallel simultaneously. Additionally, the same or different types of compressors may be connected to each of the buffers based on the formatting of the enhanced multi-channel image 122.

[0029] Additionally, and although not shown in Figure 1 , image analyzer 110 may be configured to receive and process the enhanced multi-channel image 122 including the gain map 123. In particular, image analyzer 110 may be configured to receive a given enhanced multi-channel image 122, extract a baseline image from the enhanced multi-channel image 122, and extract one or more gain maps 123 included therein. Subsequently, image analyzer 110 may utilize the baseline image and a particular one of the one or more gain maps 123 to reproduce 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 is generated based on the HDR image and an SDR image that is a counterpart of the HDR image, then the gain map 123 may be applied to the HDR image to reproduce 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 foregoing method represents only one example of the various ways in which image analyzer 110 may interact with the enhanced multi-channel image 122, and more detailed breakdown diagrams of various alternative methods are provided below in connection with Figures 2A to 2H , Figures 3A to 3F and Figures 4A to 4F .

[0030] Accordingly, Figure 1 a high-level overview of different hardware / software architectures that may be implemented by computing device 102 to implement the various techniques described herein is provided. More detailed breakdown diagrams of these techniques are now provided below in connection with Figures 2A to 2H , Figures 3A to 3F and Figures 4A to 4F .

[0031] Figures 2A to 2H A series of conceptual diagrams illustrating techniques for managing edits to different versions of an image using a gain map according to some embodiments are shown. As Figure 2AAs shown, step 210 may involve computing device 102 receiving an enhanced multi-channel HDR image 212 composed of pixels 214. In particular, pixels 214 include interleaved pixels 216 of the multi-channel HDR image (each represented as "P") and interleaved pixels 218 of the multi-channel gain map (each represented as "P'"). In this regard, the enhanced multi-channel image 212 includes information for both the multi-channel HDR image and the multi-channel gain map.

[0032] In short, it should be noted that without departing from the scope of the present disclosure, other methods may be used to store information for the multi-channel HDR image and the multi-channel gain map in the enhanced multi-channel image 212. In particular, in another method, each pixel 214 of the enhanced multi-channel image 212 may combine 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), then the corresponding pixel 214 of the enhanced multi-channel image 212 may include six channels (where the first three of the six channels store the three channels of pixel 216, and the last three of the six channels store the three channels of pixel 218).

[0033] In another method, the pixels 216 of the multi-channel HDR image may be stored as the main pixel information of the enhanced multi-channel image 212, and the pixels 218 of the multi-channel gain map may be stored as secondary (e.g., metadata-based, attachment-based, image-based, etc.) information of the enhanced multi-channel image 212. Again, these methods are merely exemplary, and any feasible method for storing the multi-channel HDR image and the multi-channel gain map within the enhanced multi-channel image 212 may be employed without departing from the scope of the present disclosure. Additionally, it should be noted that the enhanced multi-channel images 212 are not limited to storing HDR images as their baseline images. Instead, without departing from the scope of the present disclosure, a given enhanced multi-channel image 212 may store any form of image as its baseline image. For example, the enhanced multi-channel image 212 may alternatively include a multi-channel SDR image and a multi-channel gain map that enables the generation of a corresponding multi-channel HDR image (using the multi-channel SDR image and the multi-channel gain map).

[0034] Figure 2B Step 220 is shown, which involves computing device 102 extracting a multi-channel HDR image (represented as multi-channel HDR image 215 (with pixels 216)) and a multi-channel gain map (represented as multi-channel gain map 217 (with pixels 218)) from the enhanced multi-channel image 212. AsFigure 2B As shown, pixels 216 of the multi-channel HDR image 215 (and pixels 218 of the multi-channel gain map 217) can be arranged according to a row / column layout, where the subscript of each pixel (e.g., "1,1") indicates the position of the pixel according to the row and column. In Figure 2B In the example shown, 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 such that they form a square image with corresponding / overlapping pixel arrangements. However, it should be noted that the techniques described herein can be applied to multi-channel images with different layouts (e.g., disproportionate row / column counts). Additionally, and although Figure 2B not shown, each pixel (216 / 218) can be composed of three sub-pixels: a red sub-pixel (e.g., denoted as "R"), a green sub-pixel (e.g., denoted as "G"), and a blue sub-pixel (e.g., denoted as "B"). However, it should be noted that each pixel (216 / 218) can be composed of any number of sub-pixels without departing from the scope of the present disclosure.

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

[0036] Figure 2C Step 230 is shown, which involves the computing device 102 generating a multi-channel SDR image 232 by performing a multiplication operation 231 involving the multi-channel HDR image 215 and the multi-channel gain map 217. It should be noted that the multiplication operations described herein can be performed in a linear or non-linear space (e.g., by performing calculations in a non-linear gamma-encoded space). A brief overview of the manner in which the multi-channel gain map 217 is initially generated, described in detail below, provides additional context that aids in understanding Figure 2C the manner in which the multi-channel SDR image 232 is generated in

[0037] According to some embodiments, a multi-channel gain map 217 is generated (at a previous time) by comparing a multi-channel HDR image 215 with a previously complete multi-channel SDR image (i.e., the SDR counterpart of the multi-channel HDR image 215). For example, a multi-channel SDR image is 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 each other. For example, if the multi-channel HDR image 215 is generated using the EV-, EV0, and EV+ methods described herein, the multi-channel SDR image can be based on the EV0 exposure (e.g., before the EV0 exposure is combined with the EV- and EV+ exposures to generate the multi-channel HDR image 215). This method ensures 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, the pixels of the multi-channel HDR image 215 and the multi-channel SDR image can differ only in terms of the photometric values collected from the same point of the same scene (as opposed to differences in scene content due to motion resulting from the passage of time that would occur with sequentially captured exposures).

[0038] In any case, and according to some embodiments, the multi-channel gain map 217 is generated by dividing the value of each pixel of the previously complete multi-channel SDR image by the value of the corresponding pixel of the multi-channel HDR image 215 to produce a quotient. Subsequently, the corresponding quotient is 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 has a value of "5" and the corresponding pixel of the previously complete multi-channel SDR image has a value of "1", the quotient is "0.2" and is assigned to the value of the corresponding pixel 218 in the multi-channel gain map 217. In this way, and as described in more detail herein, the corresponding pixel of the previously complete multi-channel SDR image can be reproduced by multiplying the corresponding pixel 216 (having a value of "5") of the multi-channel HDR image 215 by the corresponding pixel 218 (having a value of "0.2") of the multi-channel gain map 217. In particular, the multiplication will generate a product of "1", which matches the value of "1" of the corresponding pixel of the previously complete multi-channel SDR image.

[0039] Accordingly, storing the multi-channel gain map 217 together with the multi-channel HDR image 215 can enable the previously complete multi-channel SDR image to be reproduced (as the multi-channel SDR image 232) without requiring any information about the previously complete multi-channel SDR image to be stored 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 the memory of the computing device 102 such that the multi-channel SDR image 232 can be modified and utilized. Figure 2C ​

[0040] Figure 2D Step 240 is shown, which involves the computing device 102 receiving the image modification instructions 242 and applying these image modification instructions to the multi-channel HDR image 215. The image modification instructions 242 can represent any conceivable image modification to the multi-channel HDR image 215. For example, the image modification instructions 242 can involve a mask being applied to the multi-channel HDR image 215, a filter being applied to the multi-channel HDR image 215, a photographic style being applied to the multi-channel HDR image 215, a destination display device profile being applied to the multi-channel HDR image 215, a color correction profile being applied to the multi-channel HDR image 215, and so on. It should be noted that the foregoing examples are not intended to be limiting, and the image modification instructions 242 can represent any conceivable modification that can be made to the multi-channel HDR image 215 without departing from the scope of the present disclosure.

[0041] Figure 2E Step 250 is shown, which involves the computing device 102 determining supplementary image modification instructions 242 (represented as image modification instructions 242') and applying these supplementary image modification instructions to the multi-channel SDR image 232. According to some embodiments, determining the supplementary image modification instructions 242' can involve adjusting the image modification instructions 242 based on the 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 can 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 the image modification instructions 242 can be adjusted in any manner without departing from the scope of the present disclosure. Additionally, it should be noted that the image modification instructions 242 can be applied to the multi-channel SDR image 232 first (instead of the multi-channel HDR image 215) without departing from the scope of the present disclosure. In this alternative example, the image modification instructions 242 would be adapted to take into account the differences between the multi-channel HDR image 215 and the multi-channel SDR image 232. This can involve, 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 any case, at the end of step 250, the image modification instructions 242 (the supplement to the image modification instructions 242) are applied to the multi-channel SDR image 232 such that the multi-channel HDR image 215 and the 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 the user to manually determine and apply the supplementary image modification instructions 242', which is typically a more onerous task and can produce inconsistent results.

[0043] Figure 2FStep 260 is shown, which involves the computing device 102 generating a multi-channel gain map 262 (composed of pixels 233) by performing a comparison 261 of the multi-channel HDR image 215 (modified as in Figure 2D ), with the multi-channel SDR image 232 (modified as in Figure 2E ). Here, if it is desired to enable the reproduction of the multi-channel SDR image 232 using the multi-channel HDR image 215, a first method can be utilized. In particular, the first method 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 produce a quotient. Subsequently, the corresponding quotient can in turn be assigned to the value of the corresponding pixel 263 in the multi-channel gain map 262. For example, if a pixel in the multi-channel HDR image 215 represented as "P 1,1 " has a value of "4", and a pixel in the multi-channel SDR image 232 represented as "P 1,1 " has a value of "2", then the quotient will be "0.5", and it will be assigned to the value of the pixel in the multi-channel gain map 262 represented as "P 1,1 ". In this way, and as described in more detail herein, a pixel in the multi-channel SDR image 232 represented as "P 1,1 " can be reproduced by multiplying the pixel in the multi-channel HDR image 215 represented as "P 1,1 " (with a value of "4") by the pixel in the multi-channel gain map 262 represented as "P 1,1 " (with a value of "0.5"). In particular, the multiplication will generate a product of "2", which matches the value of "2" of the pixel in the multi-channel SDR image 232 represented as "P 1,1 ". Thus, storing the multi-channel gain map 262 together with the multi-channel HDR image 215 can enable the reproduction of the multi-channel SDR image 232 independently of the multi-channel SDR image 232 itself. A more detailed description of various ways in which the multi-channel gain map 262 can be stored together with the corresponding multi-channel image is described below in connection with Figure 2G .

[0044] Alternatively, if instead it is desired to enable the reproduction of the multi-channel HDR image 232 using the multi-channel SDR image 215, a second (different) method can be utilized. In particular, the second method 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 produce a quotient. Subsequently, the corresponding quotient can in turn be assigned to the value of the corresponding pixel 263 in the multi-channel gain map 262. For example, if a pixel in the multi-channel SDR image 232 represented as "P 1,1 " has a value of "2", and a pixel in the multi-channel HDR image 215 represented as "P 1,1If the pixel of “ ” has a value of “8”, the quotient will be “4” and will be assigned to the pixel value of the multi-channel gain map 262 represented as “P 1,1 ”. In this way, and as described in more detail herein, the pixel of the multi-channel HDR image 215 represented as “P 1,1 ” can be obtained by multiplying the pixel of the multi-channel SDR image 232 represented as “P 1,1 ” (with a value of “2”) by the pixel of the multi-channel gain map 262 represented as “P 1,1 ” (with a value of “4”). In particular, the multiplication will generate a product of “8”, which matches the value of “8” of the pixel of the multi-channel HDR image 215 represented as “P 1,1 ”. Therefore, storing the multi-channel gain map 262 together with the multi-channel SDR image 232 enables the multi-channel HDR image 215 to be reproduced independently of the multi-channel HDR image 215 itself. Similarly, the following combination Figure 2G describes in more detail various ways in which the multi-channel gain map 262 can be stored together with the corresponding multi-channel image.

[0045] Briefly, it should be noted that although Figure 2F the comparisons shown (and described herein) constitute pixel-level comparisons, the embodiments are not limited thereto. Instead, without departing from the scope of the present disclosure, the pixels of the images can be compared with each other at any granularity level. For example, the sub-pixels of the multi-channel HDR image 215 and the multi-channel SDR image 232 can be compared with each other (instead of or in addition to pixel-level comparison), such that multiple gain maps are generated under different comparison methods (e.g., corresponding gain maps for each color channel).

[0046] Additionally, it should be noted that various optimizations can be employed when generating the gain map without departing from the scope of the present disclosure. For example, when two values are the same, the comparison operation can be skipped, and a single-bit value (e.g., “0”) can be assigned to the corresponding value in the gain map to minimize the size of the gain map (i.e., storage requirements). Additionally, the resolution of the gain map can be less than the resolution of the images being compared to generate the gain map. For example, the approximation of every four pixels in the first image can be compared with the approximation of every four corresponding pixels in the second image in order to generate a gain map that is one-fourth the resolution of the first and second images. This method will significantly reduce the size of the gain map, but will reduce the overall accuracy with which the first image can be reproduced based on the second image and the gain map (or vice versa). Additionally, the first and second images can be resampled in any conceivable way before generating the gain map. For example, the first and second images can undergo a local tone mapping operation before generating the gain map.

[0047] Figure 2G Illustrates step 270 according to some embodiments, which involves computing device 102 embedding multi-channel gain map 262 into multi-channel HDR image 215 or multi-channel SDR image 232. In particular, if the first method discussed above (which enables the use of multi-channel HDR image 215 and multi-channel gain map 262 to reproduce multi-channel SDR image 232) is utilized, then computing device 102 embeds multi-channel gain map 262 into multi-channel HDR image 215 (thereby generating enhanced multi-channel image 122). As Figure 2F discussed, in the first method, computing device 102 embeds multi-channel gain map 262 into multi-channel HDR image 215 (thereby generating enhanced multi-channel image 122). As Figure 2G shown, one method for embedding multi-channel gain map 262 into multi-channel HDR image 215 involves interleaving each pixel 263 (of multi-channel gain map 262) with the corresponding pixel 216 (of multi-channel HDR image 215). Alternative methods may involve embedding each pixel 263 (of multi-channel gain map 262) into the corresponding pixel 216 (of multi-channel HDR image 215) as an additional channel of pixel 216. Yet another method may involve embedding multi-channel gain map 262 as metadata stored together with multi-channel HDR image 215. It should be noted that the foregoing methods are exemplary and not intended to be restrictive, and any conceivable method may be used to store multi-channel gain map 262 (and other supplementary gain maps, if generated) together with multi-channel HDR image 215 without departing from the scope of the present disclosure. Additionally, it should be noted that if the second method discussed above in connection with 2F is utilized, a similar (i.e., complementary) process may be applied, which enables the use of multi-channel SDR image 232 and multi-channel gain map 262 to reproduce multi-channel HDR image 215.

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

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

[0050] Additionally, it should be noted that in an alternative approach, when computing device 102 determines that the image modification instruction 242 applied to the multi-channel HDR image 215 can be modified to be applied to the multi-channel gain map 217, the generation of the multi-channel SDR image 232 (described above in connection with Figure 2C ) can be omitted. In particular, the multi-channel gain map 217 can be modified to produce 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 in step 250 above in connection with Figure 2E . This method can improve the overall efficiency of computing device 102 in implementing image modification instructions because redundant modifications to the multi-channel SDR image 232 and subsequent gain map regeneration operations can be eliminated.

[0051] Figures 3A to 3F A series of conceptual diagrams illustrate techniques for managing the output of an image on a display device using a gain map according to some embodiments. As Figure 3A shown, step 310 may involve computing device 102 receiving an enhanced multi-channel image 312 composed of pixels 314. In particular, and similar to the scenario described above in connection with Figure 2A , the pixels 314 include interleaved pixels 316 of a first version of the multi-channel image (each represented as "P") and interleaved pixels 318 of the multi-channel gain map (each represented as "P"). In this regard, the enhanced multi-channel image 312 includes information for both the first version of the multi-channel image and the multi-channel gain map. Also, it should be noted that Figure 3A the embedding method shown is not intended to be restrictive, and any conceivable method can be used to combine the information for 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 the present disclosure.

[0052] Figure 3B Step 320 is shown, which involves the computing device 102 extracting a first version of the multi-channel image (represented as multi-channel image 315) and a multi-channel gain map (represented as multi-channel gain map 317) from the enhanced multi-channel image 312. The same or similar techniques described above in connection with Figure 2B the description can be used to perform this extraction. In any 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 into a memory (e.g., random access memory (RAM)) such that they can be easily accessed and manipulated by the computing device 102.

[0053] Figure 3C Step 330 is shown, which involves the computing device 102 identifying a headroom level 334 of a second version of the image based on the current brightness setting 333 of a display device 332 that is communicatively coupled to the computing device 102. According to some embodiments, the current brightness setting 333 of the display device 332 may affect the dynamic range of colors / light intensities 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 colors / light intensities that the display device 332 can accurately output decreases; while when the brightness setting of the display device decreases, the dynamic range of colors / light intensities that the display device 332 can accurately output increases. In this regard, it may be beneficial to scale the range of colors / light intensities of a given image, which can be performed using the aforementioned headroom level 334 based on the current brightness of the display device. This approach provides various benefits because the task of the display device is not to display an image having colors / light intensities that fall outside the current range that the display device can display.

[0054] Without departing from the scope of the present disclosure, additional factors may be considered when generating the headroom level 334. 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) (similar to the current brightness setting 333 of the display device 332, which can affect the colors / light intensities that can be output by the display device 332 and accurately perceived by humans). In another example, the headroom level 334 may be based on loss level information associated with the display device 332. For example, the loss level information (i.e., pixel-level usage mapping) may indicate that certain pixels of the display device 332 are utilized at a higher frequency relative to other pixels of the display device 332, thereby making them less capable of accurately displaying colors / light intensities. It should be noted that the foregoing examples are not intended to be limiting, and any information that affects the ability of the display device 332 to accurately display colors / light intensities can 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 clearance level 334 represents a single value (e.g., weight) to be applied to the multi-channel gain map 317 before generating a second version of the multi-channel image using the multi-channel gain map 317 (details of which are described below in conjunction with Figure 3D . In another approach, the clearance level 334 may take the form of a set of weights that are applied separately and correspondingly to the multi-channel gain map 317. The method may include, for example, corresponding weights for each pixel included in the enhanced multi-channel image 312 (1:1 ratio), corresponding weights for every two pixels included in the enhanced multi-channel image 312 (1:2 ratio), corresponding weights for every N pixels included in the enhanced multi-channel image 312 (1:N ratio). Again, it should be noted that the foregoing examples are not intended to be limiting, and without departing from the scope of the present disclosure, the clearance level 334 may take any form to modify the multi-channel gain map 317 at any level of granularity.

[0056] In any case and as Figure 3C shown, step 330 involves the computing device 102 establishing a modified multi-channel gain map 336 (which includes pixels 337) based on the clearance level 334. As Figure 3C shown, the pixels 337 of the multi-channel gain map 336 are represented as "P" to indicate that they have been modified relative to the pixels 318 of the multi-channel gain map 317 represented as "P'".

[0057] Figure 3D Step 340 is shown, which involves the computing device 102 generating a second version of the multi-channel image by performing a multiplication operation 341 that involves the first version of the multi-channel image (i.e., the multi-channel image 315) and the modified multi-channel gain map 336. As Figure 3D shown, techniques similar to those described above in conjunction with Figure 2C may be employed to perform the foregoing generation of the modified multi-channel gain map 336. In any case, this generation results in a second version of the multi-channel image that can be output on the display device 332 (shown in Figure 3D as the multi-channel image 342 (which includes pixels 343)). Thus, Figure 3E Step 350 is shown, which involves the computing device 102 causing the second version of the multi-channel image (i.e., the multi-channel image 342) to be displayed on the display device 332. In this regard, the multi-channel image 342 represents a modified version of the multi-channel image 315 that has been optimized for display on the display device 332 based on the clearance level 334 described above in conjunction with Figure 3C .

[0058] Additionally, Figure 3FIllustrated is a method 360 for managing the output of an image on a display device using gain mapping according to some embodiments. As Figure 3F shown, method 360 begins at step 362, where computing device 102 accesses an enhanced image that includes a first version of the image and a plurality of gain maps. At step 362, computing device 102 identifies a headroom level of a second version of the image based on the current brightness setting of the display device (e.g., as described above in connection with Figure 3C ). At step 364, computing device 102 identifies a particular gain map corresponding to the headroom level among the plurality of gain maps. At step 366, computing device 102 uses the first version of the image and the particular gain map to generate a second version of the image. At step 368, computing device 102 causes the second version of the image to be displayed on the display device (e.g., as described above in connection with Figure 3E ).

[0059] Additionally, it should be noted that the enhanced multi-channel image may include a plurality of gain maps spanning a range of brightness levels that can be presented by the display device. For example, if a given display device is capable of displaying twenty different brightness levels, the enhanced multi-channel image may include twenty different gain maps, where each gain map corresponds to a respective one of the twenty different brightness levels. In this regard, the gain map modification operations discussed above in connection with Figures 3A to 3F can be replaced with a simple lookup (and application) of the appropriate gain map corresponding to the current brightness level. This method can improve 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. Additionally, it should be noted that the plurality of gain maps may be based on other display factors discussed herein, including external lighting conditions relative to the display. This can include, for example, identifying the 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 method is not intended to be limiting, and without departing from the scope of the present disclosure, the enhanced multi-channel image may include any number of gain maps based on any number of factors affecting the ability to display output.

[0060] Figures 4A to 4F Illustrated are a series of conceptual diagrams for generating a gain map that enables the generation of a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and the gain map. As Figure 4AAs shown, step 410 involves computing device 102 accessing a multi-channel HDR image 411 (which, as described herein, includes pixels 412 and sub-pixels 414). This can involve, for example, computing device 102 receiving a request to import the multi-channel HDR image 411 into a photo library, for example, managed by computing device 102 and accessible by a user of computing device 102. This can occur, for example, when a user imports an HDR image from a high-end digital camera (with HDR capabilities), when a user receives an HDR image from someone else, etc. In these scenarios, it may be desirable to be able to accurately display an SDR version of the HDR image when appropriate, especially when a display device communicatively coupled to computing device 102 is only capable of displaying the colors / luminance of SDR images. This may also be desirable when HDR images and SDR images are displayed as thumbnail images next to each other, which often causes the user to perceive the HDR image as too bright and the SDR image as too dark (even when they are properly displayed on an HDR-capable display). In such a scenario, computing device 102 utilizes gain mapping to reduce (partially or wholly) the HDR image to a range that conforms to the SDR image (and / or vice versa) in order to balance the overall intensity of the thumbnails.

[0061] Accordingly, Figure 4B Step 420 is shown, which involves computing device 102 generating a multi-channel SDR image 422 (which includes pixels 423) by applying a global tone mapping operation 421 to the multi-channel HDR image 411. Here, given that a given multi-channel HDR image 411 is different from the enhanced multi-channel images discussed herein and does not (yet) include a multi-channel gain mapping that enables the generation of a corresponding multi-channel SDR image, this generation is necessary. However, as described herein, the global tone mapping operation 421 can be used to generate an approximation of the corresponding multi-channel SDR image. In particular, the global tone mapping operation can involve mapping an extended HDR color range to a more limited SDR color range, endeavoring to reduce the introduction of artifacts (such as banding effects due to a reduced bit depth that reduces the granularity of displayable gradient transitions). It should be noted that any alternative (or additional) image-based process / modification can be applied to the multi-channel HDR image 411 without departing from the scope of the present disclosure.

[0062] In any case, Figure 4C Step 430 is shown, which involves computing device 102 generating a multi-channel gain mapping 434 (which includes pixels 435) by performing a comparison 432 of the multi-channel HDR image 411 and the multi-channel SDR image 422. As described above in connection with Figure 2FThe same or similar techniques described above can be used for comparison 432 (specifically, the first method which involves dividing the value of each pixel of the multi-channel SDR image 422 by the value of the corresponding pixel of the multi-channel HDR image 411 to produce a quotient).

[0063] Next, Figure 4D Step 440 is shown, which involves the computing device 102 embedding the multi-channel gain map 434 into the multi-channel HDR image 411. The same or similar techniques described above in connection with Figure 2G can be used to perform step 440, as Figure 4D shown, which involves injecting information about the pixels 435 of the multi-channel gain map 434 into the multi-channel HDR image 411 (e.g., as adjacent pixel information, extended channel information, additional metadata information, separate image information, etc.). At this point, the multi-channel HDR image 411 effectively transforms into an enhanced multi-channel image 122 that includes the multi-channel HDR image 411 and the multi-channel gain map 434. Additionally, the multi-channel SDR image 422 can be reproduced using the multi-channel HDR image 411 and the multi-channel gain map 434, such that there is no longer a need to retain the multi-channel SDR image 422. Therefore, Figure 4E Step 450 is shown, which involves the computing device 102 discarding the multi-channel SDR image 422.

[0064] Additionally, Figure 4F A method 460 for generating a gain map is shown according to some embodiments, which enables the generation of a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and the gain map. As Figure 4F shown, method 460 begins at step 462, where the computing device 102 accesses a high dynamic range (HDR) image (e.g., as described above in connection with Figure 4A ). At step 464, the 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 connection with Figure 4B ).

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

[0066] Figure 5 A detailed view of a computing device 500 that can be used to implement various techniques described herein is shown, according to some embodiments. In particular, this detailed view shows the various components that may be included in the computing device 102 described Figure 1 above. As Figure 5 shown, the computing device 500 may include a processor 502 that represents a microprocessor or a 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 buttons, keypads, dials, touchscreens, audio input interfaces, visual / image capture input interfaces, inputs in the form of 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 a storage device 540, the processor 502, and a controller 513. The controller 513 may be used to interact with and control different equipment via an equipment control bus 514. The computing device 500 may also include a network / bus interface 511 coupled to a data link 512. In the case of a wireless connection, the network / bus interface 511 may include a wireless transceiver.

[0067] As described above, the computing device 500 further includes a storage device 540, which may include a single disk (e.g., a hard disk) or a collection of disks. In some embodiments, the storage device 540 may include flash memory, semiconductor (solid-state) memory, etc. 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 programs, utilities, or processes to be executed in a non-volatile manner. The RAM 520 may provide volatile data storage and store instructions related to the operation of application programs (e.g., the image analyzer 110 / gain map generator 120) executed on the computing device 500.

[0068] The techniques described herein include a first technique for managing edits to different versions of an image using a gain map. According to some embodiments, the first technique may be implemented by a computing device and includes the following steps: (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) using the HDR image and the gain map to generate a standard dynamic range (SDR) image; (4) receiving a first modification instruction and applying the first modification instruction to the HDR image; (5) generating a second modification instruction based at least on the first modification instruction; (6) applying the second modification instruction to the SDR image; (7) generating a second gain map by comparing the HDR image with 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 a second modification instruction based at least on the first modification instruction includes: (1) identifying at least one change to the HDR image caused by applying the first modification instruction; and (2) determining how to apply a complementary at least one change to the SDR image, wherein applying the second modification instruction to the SDR image results in a complementary at least one change to the SDR image.

[0070] According to some embodiments, the first technique may further include the following steps before accessing the HDR image: (1) receiving at least a first exposure of a scene and a second exposure of the scene, wherein the first exposure and the second exposure are captured at a bit depth for storing the HDR image; and (2) processing the first exposure and the second exposure 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 the 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 the 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 the 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] The techniques described herein include a second technique for managing the output of an image on a display device using multiple gain maps. According to some embodiments, the second technique may be implemented by a computing device and includes the following steps: (1) accessing an enhanced image that includes a first version of the image and multiple gain maps; (2) identifying a headroom level of a second version of the image based on a current brightness setting of the display device; (3) identifying a specific gain map corresponding to the headroom level among the multiple gain maps; (4) using the first version of the image and the specific gain map to generate a second version of the image; and (5) causing the second version of the image to be displayed on the display device.

[0073] According to some embodiments, the headroom level is also based on the color gamut capacity of the display device and / or external lighting conditions relative to the display device. According to some embodiments, at least one light sensor communicatively coupled to the computing device is used to detect the external lighting conditions. 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 accurately output 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 a 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 a first exposure, a second exposure, and a third exposure 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 the generation of a standard dynamic range (SDR) image based on a high dynamic range (HDR) image and the gain map. According to some embodiments, the third technique may be implemented by a computing device and includes the following steps:

[0075] (1) accessing the 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 into the HDR image; (5) receiving a request to view the SDR version of the HDR image; and (6) providing the SDR version of the HDR image using the HDR image and the gain map.

[0076] According to some embodiments, a global tone mapping operation reduces the bit depth of each pixel included in an HDR image. According to some embodiments, comparing an SDR image with an HDR image includes, for each pixel of the SDR image: (i) identifying the 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 into the HDR image includes, for each pixel of the gain map: (i) identifying the corresponding pixel in the HDR image, and (ii) storing the value of the pixel as supplementary information in the corresponding pixel. According to some embodiments, embedding the gain map into the HDR image includes: storing the gain map as metadata accompanying the HDR image.

[0077] According to some embodiments, providing an SDR version of an HDR image using the HDR image and the gain map includes, for each pixel of the gain map: multiplying the pixel by the corresponding pixel in the HDR image to produce the corresponding pixel of the SDR version of the HDR image.

[0078] Aspects, embodiments, implementations, or features of the described embodiments may be used singly or in any combination. Aspects of the described embodiments may be implemented by software, hardware, or a combination of hardware and software. The described embodiments may also be embodied as computer-readable code on a computer-readable medium. A computer-readable medium is any data storage device that can store data, which can then be read by a computer system. Examples of the computer-readable medium include read-only memory, random access memory, CD-ROM, DVD, magnetic tape, hard disk drive, solid-state drive, and optical data storage device. The computer-readable medium may also be distributed over network-coupled computer systems so that the computer-readable code is stored and executed in a distributed fashion.

[0079] For purposes of explanation, the foregoing description uses specific names to provide a thorough understanding of the described embodiments. However, it will be apparent to those skilled in the art that no specific details are required in order to practice the described embodiments. Thus, the foregoing description of specific embodiments is presented for purposes of illustration and description. The foregoing description is not intended to be exhaustive or to limit the described embodiments to the precise forms disclosed. It will be apparent to those of ordinary skill in the art that many modifications and variations are possible in light of the above teachings.

Claims

1. A method for managing the editing of different versions of an image using a gain map, the method comprising, at a computing device: 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; Using the HDR image and the gain map to generate a standard dynamic range (SDR) image; Receiving a first modification instruction and applying the first modification instruction to the HDR image; Generating a second modification instruction based at least on the first modification instruction; Applying the second modification instruction to the SDR image; Generating a second gain map by comparing the HDR image with the SDR image or vice versa; and Embedding the second gain map into the HDR image or the SDR image.

2. 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 manage the editing of different versions of an image using a gain map by performing steps including: 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; Using the HDR image and the gain map to generate a standard dynamic range (SDR) image; Receiving a first modification instruction and applying the first modification instruction to the HDR image; Generating a second modification instruction based at least on the first modification instruction; Applying the second modification instruction to the SDR image; Generating a second gain map by comparing the HDR image with the SDR image or vice versa; and Embedding the second gain map into the HDR image or the SDR image.

3. A computing device configured to manage the editing of different versions of an image using a gain map, the computing device comprising: At least one processor; And At least one memory storing instructions that, when executed by the at least one processor, cause the computing device to perform steps including: 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; Using the HDR image and the gain map to generate a standard dynamic range (SDR) image; Receiving a first modification instruction and applying the first modification instruction to the HDR image; Generating a second modification instruction based at least on the first modification instruction; Applying the second modification instruction to the SDR image; Generating a second gain map by comparing the HDR image with the SDR image or vice versa; and Embedding the second gain map into the HDR image or the SDR image.

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

Images