A technique for using gain maps to manage the changing state of an image.

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] Embodiments described herein describe techniques for utilizing gain maps to manage the changing state of an image. In particular, gain maps can be used to provide various features, including generating a first version of the image and a second version of the image by utilizing the gain map. [Background technology]

[0002] The dynamic range of an image refers to the range of pixel values ​​between the brightest and darkest parts of an 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 what the human eye can perceive from the same scene. This limited range is usually called the standard dynamic range (SDR) in the world of digital photography.

[0003] Despite the limitations of image sensors mentioned above, improvements in photographic 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 an image, 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 respect, a single HDR image has a wider dynamic range of luminance compared to what could be captured in any other way at 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 technology. However, the vast majority of display devices currently in use (and continuing to be manufactured) can only display SDR images. Therefore, devices with SDR-limited displays that receive HDR images must perform various tasks to convert the HDR images to their SDR equivalents (i.e., downgrade them). Conversely, devices with HDR-enabled displays that receive SDR images may attempt to perform various tasks to convert the SDR images to their HDR equivalents (i.e., upgrade them).

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

[0006] Therefore, what is needed is a technique that allows for efficient and accurate transitions between different states of an image. For example, it is desirable to be able to downgrade an HDR image to its true SDR counterpart (and vice versa) without relying on the aforementioned (and inadequate) conversion techniques. [Overview of the project]

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

[0008] One embodiment describes a method for managing editing for different versions of an image using a gain map. The method includes: (1) accessing an enhanced image including a high dynamic range (HDR) image and a gain map; (2) extracting the HDR image and gain map from the enhanced image; (3) generating a standard dynamic range (SDR) image using the HDR image and gain map; (4) receiving and applying a first modification instruction to the HDR image; (5) generating a second modification instruction based on at least 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 describes a method for utilizing a gain map to manage the output of an image on a display device. The method includes (1) accessing an enhanced image including a first version of the image and a gain map; (2) identifying the headroom level of a second version of the image based on the current brightness setting of the display device; (3) establishing a modified gain map based on the headroom level; (4) generating a 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] Another embodiment describes a method 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 a gain map, according to several embodiments. This 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 into the HDR image; (5) receiving a request to view an SDR version of the HDR image; and (6) providing an SDR version of the HDR image using the HDR image and the gain map.

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

[0012] Other aspects and advantages of the present invention will become apparent from the following detailed description, with the use of accompanying drawings illustrating the principles of the embodiments described, for example.

[0013] This disclosure will be readily understood by the following detailed description in conjunction with the attached drawings, where similar reference numerals indicate similar structural elements. [Brief explanation of the drawing]

[0014] [Figure 1] This document outlines computing devices that can be configured to perform various technologies described herein, according to several embodiments.

[0015] [Figure 2A]A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2B] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2C] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2D] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2E] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2F] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2G] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown. [Figure 2H] A series of conceptual diagrams of techniques using a gain map to manage editing for different versions of an image, according to some embodiments, are shown.

[0016] [Figure 3A] A series of conceptual diagrams of techniques using a gain map to manage the output of an image on a display device, according to some embodiments. [Figure 3B] A series of conceptual diagrams of techniques using a gain map to manage the output of an image on a display device, according to some embodiments. [Figure 3C] A series of conceptual diagrams of techniques using a gain map to manage the output of an image on a display device, according to some embodiments. [Figure 3D] 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. [Figure 3E] 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. [Figure 3F] 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.

[0017] [Figure 4A] 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] 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] 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] 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] 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]This is a series of conceptual diagrams for generating gain maps that enable the generation of standard dynamic range (SDR) images based on high dynamic range (HDR) images and gain maps, according to several embodiments.

[0018] [Figure 5] Detailed diagrams of computing devices that can be used to perform the various techniques described herein, according to several embodiments, are shown. [Modes for carrying out the invention]

[0019] Representative applications of the method and apparatus described herein are described in this section. These examples are provided solely for the purpose of adding context and aiding in the understanding of the embodiments described. It will therefore be apparent to those skilled in the art that the embodiments described may be carried out without some or all of these specific details. In other examples, well-known process steps are not described in detail in order to avoid unnecessarily obscuring the embodiments described. Other applications are possible, and therefore the following examples should not be construed as limiting.

[0020] In the following "Modes for Carrying Out the Invention," reference is made to the accompanying drawings, which illustrate specific embodiments of the embodiments described, forming part of the description. These embodiments are described in sufficient detail, and those skilled in the art will be able to carry out the embodiments described. However, these embodiments are not limiting, and other embodiments may be used and modified as long as they do not deviate from the spirit and scope of the embodiments described.

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

[0022] Figure 1 shows an overview of a computing device 102 that can be configured to perform various techniques described herein. As shown in Figure 1, the computing device 102 may include a processor 104, volatile memory 106, and non-volatile memory 124. A more detailed breakdown of exemplary hardware components that may be included in the computing device 102 is shown in Figure 5, and it should be noted that these components have been omitted from the diagram in Figure 1 simply for simplification. For example, the computing device 102 may include additional non-volatile memory (e.g., solid-state drives, hard 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) (not shown in Figure 1) can be loaded into the volatile memory 106, and the OS can run various applications that collectively enable the implementation of various techniques described herein. For example, these applications may 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 Figure 1), and the like.

[0023] As shown in Figure 1, the volatile memory 106 can be configured to receive a multichannel image 108. The multichannel image 108 can be provided, for example, by a digital imaging unit (not shown in Figure 1) configured to capture and process a digital image. According to some embodiments, the multichannel image 108 can consist of a set of pixels, where each pixel in the set of pixels includes a group of subpixels (e.g., red subpixels, green subpixels, blue subpixels, etc.). Note that the term “subpixel” as used herein may be synonymous with the term “channel.” Note also that the multichannel image 108 may have different resolutions, layouts, bit depths, etc., without departing from the scope of this disclosure.

[0024] According to some embodiments, a given multichannel image 108 can represent a standard dynamic range (SDR) image comprising a single exposure of a scene collected and processed by a digital imaging unit. The given multichannel image 108 can also represent a high dynamic range (HDR) image comprising multiple exposures of a scene collected and processed by a digital imaging unit. To generate an HDR image, the digital imaging unit may capture the scene under three different exposure brackets, often referred to as "EV0," "EV-," and "EV+." Generally, the EVO image corresponds to the normal / ideal exposure of the scene (typically captured using the digital imaging unit's automatic exposure settings). 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 incorporating a wider range of luminances than that of an SDR image. It should be noted that the multichannel image 108 described herein is not limited to SDR / HDR images. Conversely, the multichannel image 108 can represent any form of digital image (e.g., a scanned image, a computer-generated image, etc.) without departing from the scope of this disclosure.

[0025] As shown in Figure 1, the multichannel image 108 can be provided to the image analyzer 110 (optionally). According to some embodiments, the image analyzer 110 may include various components configured to process / modify the multichannel 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 multichannel image), a color correction unit 116 (e.g., configured to perform global / local color correction in the multichannel image), and a sharpening unit 118 (e.g., configured to perform global / local sharpening correction in the multichannel image). Note that the image analyzer 110 is not limited to the processing units described above, and the image analyzer 110 may incorporate any number of processing units configured to perform any processing / modification on the multichannel image 108 without departing from the scope of this disclosure.

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

[0027] In either case, as will be described in more detail herein, the gain map generator 120 can generate a gain map 123 based on the two multichannel images 108 upon receiving two multichannel images 108. The gain map generator 120 can then store the gain map 123 in one of the two multichannel images 108 to generate an enhanced multichannel image 122. It should be further noted that the gain map generation technique can be performed at any time upon receiving the multichannel image on which the gain map is based. For example, the gain map generator 120 may be configured to postpone the generation of the gain map when the digital imaging unit is actively in use to ensure that adequate processing resources are available so as not to impose a slowdown on the user. A more detailed breakdown of how the gain map generator 120 can generate the gain map 123 is provided below in relation to Figures 2A-2H, 3A-3F, and 4A-4F.

[0028] In addition, although not shown in Figure 1, one or more compressors can be implemented on the computing device 102 to compress the enhanced multichannel image 122. For example, the compressors can be Lempel-Ziv-Welch (LZW) based compressors, other types of compressors, or combinations of compressors. Furthermore, the compressors can be implemented in any way to establish the most efficient environment for compressing the enhanced multichannel image 122. For example, multiple buffers can be instantiated (pixels can be preprocessed in parallel), and each buffer can be combined with a separate compressor to compress the buffers simultaneously in parallel. Furthermore, based on the format of the enhanced multichannel image 122, the same or different types of compressors can be combined with each buffer.

[0029] Furthermore, although not shown in Figure 1, the image analyzer 110 can be configured to receive and process an enhanced multichannel image 122 containing a gain map 123. In particular, the image analyzer 110 can be configured to receive a given enhanced multichannel image 122, extract a baseline image from the enhanced multichannel image 122, and extract one or more gain maps 123 contained therein. The image analyzer 110 can then use the baseline image and a specific one of the one or more gain maps 123 to reconstruct 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 its HDR counterpart, an SDR image, the gain map 123 can be applied to the HDR image to reconstruct the SDR image (without requiring the SDR image itself to be included in the enhanced multichannel image 122). The method described above represents only one embodiment of various ways in which the image analyzer 110 can interact with the enhanced multichannel image 122. It should be noted that a more detailed breakdown of various alternative methods is provided below in conjunction with Figures 2A to 2H, 3A to 3F, and 4A to 4F.

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

[0031] Figures 2A to 2H show a series of conceptual diagrams of techniques that utilize gain maps to manage editing for different versions of an image, according to several embodiments. As shown in Figure 2A, step 210 may include the computing device 102 receiving an enhanced multichannel image 212 consisting of pixels 214. In particular, pixels 214 include interleaved pixels 216 (each indicated as "P") of the multichannel HDR image, as well as interleaved pixels 218 (each indicated as "P'") of the multichannel gain map. In this regard, the enhanced multichannel image 212 contains information from both the multichannel HDR image and the multichannel gain map.

[0032] In short, it should be noted that information from a multi-channel HDR image and a multi-channel gain map can be stored in an enhanced multi-channel image 212 using other methods without departing from the scope of this disclosure. In particular, under other methods, each pixel 214 of the enhanced multi-channel image 212 can 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 contains three channels (e.g., red, green, and blue) and each pixel 218 of the multi-channel gain map contains three channels (e.g., red, green, and blue), then the corresponding pixel 214 of the enhanced multi-channel image 212 can contain 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] Alternatively, pixels 216 of a multichannel HDR image can be stored as primary pixel information in the enhanced multichannel image 212, and pixels 218 of a multichannel gain map can be stored as secondary (e.g., metadatabase, attachment-based, image-based, etc.) information in the enhanced multichannel image 212. Again, these methods are illustrative, and any feasible method for storing multichannel HDR images and multichannel gain maps within the enhanced multichannel image 212 can be employed without departing from the scope of this disclosure. Furthermore, it should be noted that the enhanced multichannel image 212 is not limited to storing HDR images as its baseline images. Conversely, a given enhanced multichannel image 212 can store any form of image as its baseline image without departing from the scope of this disclosure. For example, the enhanced multichannel image 212 could instead include a multichannel SDR image and a multichannel gain map that enables the generation of a corresponding multichannel HDR image (using the multichannel SDR image and multichannel gain map).

[0034] Figure 2B shows step 220, in which the computing device 102 extracts a multichannel HDR image (shown as a multichannel HDR image 215 (having pixels 216)) and a multichannel gain map (shown as a multichannel gain map 217 (having pixels 218)) from an enhanced multichannel image 212. As shown in Figure 2B, the pixels 216 of the multichannel HDR image 215 (and the pixels 218 of the multichannel gain map 217) can be arranged according to a row / column layout, and the subscripts for each pixel (e.g., "1,1") indicate the location of the pixel according to the row and column. In the example shown in Figure 2B, the pixels of the multichannel HDR image 215 and the multichannel gain map 217 are arranged in equal numbers 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 multichannel images having different layouts (e.g., unbalanced row / column counts). Furthermore, although not shown in Figure 2B, each pixel (216 / 218) may consist of three subpixels: a red subpixel (e.g., denoted as "R"), a green subpixel (e.g., denoted as "G"), and a blue subpixel (e.g., denoted as "B"). However, it should be noted that each pixel (216 / 218) may consist of any number of subpixels without departing from the scope of this 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] Figure 2C shows step 230, in which the computing device 102 generates a multichannel SDR image 232 by performing a multiplication operation 231 including a multichannel HDR image 215 and a multichannel gain map 217. Note that the multiplication operation described herein may be performed in linear or nonlinear space (for example, by performing the calculation in a nonlinear gamma coding space). An outline of how the multichannel gain map 217 was initially generated (described in detail below) provides additional context to help understand how the multichannel SDR image 232 is generated in Figure 2C.

[0037] According to some embodiments, the multichannel gain map 217 is generated (previously) by comparing the multichannel HDR image 215 with a previous, untouched multichannel SDR image, i.e., the SDR counterpart of the multichannel HDR image 215. For example, the multichannel SDR image may be generated based on a single exposure capture of the same scene captured by the multichannel HDR image 215, such that the multichannel SDR image and the multichannel HDR image 215 are substantially related to each other. For example, if the multichannel HDR image 215 is generated using the EV-, EV0, and EV+ techniques described herein, the multichannel SDR image may be based on the EV0 exposure (for example, before the EV0 exposure is merged with the EV- and EV+ exposures to generate the multichannel HDR image 215). This technique can ensure that both the multichannel HDR image 215 and the multichannel SDR image correspond to the same scene at the same moment. 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 luminance collected from the same point in the same scene (as opposed to differences in the scene content due to motion resulting from the passage of time through continuously captured exposures).

[0038] In any case, according to some embodiments, the multi-channel gain map 217 is generated by dividing the value of each pixel in the previous untouched multi-channel SDR image by the value of the corresponding pixel in 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 in the multi-channel HDR image 215 has a value of "5" and the corresponding pixel in the previous untouched 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. Thus, as will be described in more detail herein, the corresponding pixel in the previous untouched multi-channel SDR image can be reconstructed by multiplying the corresponding pixel 216 in the multi-channel HDR image 215 (having a value of "5") by the corresponding pixel 218 in the multi-channel gain map 217 (having a value of "0.2"). In particular, the multiplication produces a product of "1", which matches the value "1" of the corresponding pixel in the previous untouched multi-channel SDR image.

[0039] Therefore, by storing the multi-channel gain map 217 together with the multi-channel HDR image 215, the previous untouched multi-channel SDR image can be reproduced in Figure 2C (as the multi-channel SDR image 232) without the need to store information about the previous untouched 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 the memory of the computing device 102, making it possible to modify and use the multi-channel SDR image 232.

[0040] Figure 2D shows step 240, in which the computing device 102 receives an image modification instruction 242 and applies it to the multi-channel HDR image 215. The image modification instruction 242 can represent any conceivable image modification to the multi-channel HDR image 215. For example, the image modification instruction 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, or applying a color correction profile to the multi-channel HDR image 215. Note that the above examples are not intended to limit the scope, and the image modification instruction 242 can represent any conceivable modification that can be made to the multi-channel HDR image 215 without departing from the scope of this disclosure.

[0041] Figure 2E shows step 250, in which the computing device 102 determines and applies a complementary image correction instruction 242 (indicated as image correction instruction 242') to the multichannel SDR image 232. According to some embodiments, determining a complementary image correction instruction 242' may include adjusting the image correction instruction 242 based on differences identified between the multichannel HDR image 215 and the multichannel SDR image 232. For example, an instruction specific to the higher bit range of the multichannel HDR image 215 may be adapted according to the lower bit range of the multichannel SDR image 232. It should be noted that the correction techniques are not limited to the examples described above, and the image correction instruction 242 may be adjusted to any extent without departing from the scope of the disclosure. It should be further noted that, without departing from the scope of the disclosure, the image correction instruction 242 may be applied first to the multichannel SDR image 232 (instead of the multichannel HDR image 215). In this alternative example, the image correction command 242 is adapted to take into account the difference between the multi-channel HDR image 215 and the multi-channel SDR image 232. This could include, for example, adjusting the image correction command 242 to take into account the higher bit depth available in the multi-channel HDR image 215.

[0042] In either case, at the end of step 250, an image correction command 242' (complementing image correction command 242) is applied to the multichannel SDR image 232, resulting in the multichannel HDR image 215 and the multichannel SDR image 232 being edited in a similar manner (taking into account their differences / limitations). This technique offers several benefits, including eliminating the need for the user to manually determine and apply complementary image correction commands 242', which is typically a cumbersome and potentially inconsistent task.

[0043] Figure 2F shows step 260, in which the computing device 102 generates a multichannel gain map 262 (composed of pixels 233) by performing a comparison 261 between a multichannel HDR image 215 (modified in Figure 2D) and a multichannel SDR image 232 (modified in Figure 2E). Here, if it is desirable to enable the multichannel SDR image 232 to be reproduced using the multichannel HDR image 215, a first method may be used. In particular, the first method involves dividing the value of each pixel in the multichannel SDR image 232 by the value of the corresponding pixel in the multichannel HDR image 215 to generate a quotient. Each quotient can then be assigned to the value of the corresponding pixel 263 in the multichannel gain map 262. For example, the "P 1,1 The pixels indicated by have a value of "4", and the "P" in the multi-channel SDR image 232 1,1 If the pixel indicated by " has a value of "2", the quotient will be "0.5", and the "P" of the multi-channel gain map 262 1,1 It is assigned to the pixel value indicated by ". In this way, and as will be described in more detail herein, the multichannel SDR image 232 "P 1,1 The pixels indicated by "P" are the "P" pixels of the multi-channel HDR image 215. 1,1 The pixel indicated by " (having a value of "4") is the "P" of the multi-channel gain map 262. 1,1 It can be reproduced by multiplying by the pixel indicated by " (which has a value of "0.5"). In particular, the multiplication is performed on the "P" of the multichannel SDR image 232. 1,1 This generates a product "2" that matches the pixel value "2" indicated by ". Therefore, storing the multichannel gain map 262 together with the multichannel HDR image 215 makes it possible for the multichannel SDR image 232 to be reproduced independently of the multichannel SDR image 232 itself. A more detailed explanation of the various ways in which the multichannel gain map 262 may be stored together with the corresponding multichannel image is described below in relation to Figure 2G.

[0044] Alternatively, if it is desirable to enable the multi-channel HDR image 215 to be played back using the multi-channel SDR image 232, a second (different) technique may be utilized. In particular, the second technique 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. Next, each quotient can be assigned to the value of the corresponding pixel 263 within the multi-channel gain map 262. For example, if the pixel indicated by "P" in the multi-channel SDR image 232 has a value of "2", and the pixel indicated by "P" in the multi-channel HDR image 215 has a value of "8", the quotient is "4" and is assigned to the value of the pixel indicated by "P" in the multi-channel gain map 262. In this way, and as described in more detail herein, the pixel indicated by "P" in the multi-channel HDR image 215 can be played back by multiplying the pixel indicated by "P" (having a value of "2") in the multi-channel SDR image 232 by the pixel indicated by "P" (having a value of "4") in the multi-channel gain map 262. In particular, the multiplication generates a product "8" that matches the value "8" of the pixel indicated by "P" in the multi-channel HDR image 215. Thus, storing the multi-channel gain map 262 together with the multi-channel SDR image 232 can enable the multi-channel HDR image 215 to be played back independently of the multi-channel HDR image 215 itself. Again, a more detailed description of the 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 FIG. 2G.

[0045] ​​​​​​​​​​​​​​In short, the comparison shown in Figure 2F (and described herein) constitutes a pixel-level comparison, but it should be noted that embodiments are not limited in this way. Conversely, pixels in an image can be compared to one another at any level of granularity without departing from the scope of this disclosure. For example, subpixels of a multi-channel HDR image 215 and a multi-channel SDR image 232 can be compared to one another (instead of or in addition to a pixel-level comparison) such that multiple gain maps are generated under different comparison methods (e.g., separate gain maps for each channel of color).

[0046] In addition, it should be noted that various optimizations can be employed when generating the gain map without departing from the scope of this disclosure. For example, if two values ​​are identical, 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., the memory requirement). 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, to generate a gain map that is one-quarter the resolution of the first and second images, a 4-pixel approximation in the first image can be compared to a corresponding 4-pixel approximation in the second image. This technique substantially reduces the size of the gain map but reduces the overall accuracy to which the first image can be reconstructed from the second image and the gain map (or vice versa). Furthermore, 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 local tone mapping operations before generating the gain map.

[0047] Figure 2G shows a step 270 in which, according to several embodiments, the computing device 102 embeds a multi-channel gain map 262 into a multi-channel HDR image 215 or a multi-channel SDR image 232. In particular, when the first technique described above in relation to Figure 2F is used, which enables the reproduction of a multi-channel SDR image 232 using the multi-channel HDR image 215 and the multi-channel gain map 262, the computing device 102 embeds the multi-channel gain map 262 into the multi-channel HDR image 215 (thus generating an enhanced multi-channel image 122). As shown in Figure 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 respect to its corresponding pixel 216 (of the multi-channel HDR image 215). An alternative technique 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 technique may include embedding the multi-channel gain map 262 as metadata stored with the multi-channel HDR image 215. Note that the techniques described above are illustrative and not intended to limit, and that the multi-channel gain map 262 (and any other supplemental gain maps, if generated) may be stored with the multi-channel HDR image 215 using any conceivable technique without departing from the scope of this disclosure. Furthermore, note that similar (i.e., complementary) procedures may be applied when the second technique described above is used in relation to 2F, enabling the reproduction of the multi-channel HDR image 215 using the multi-channel SDR image 232 and the multi-channel gain map 262.

[0048] Figure 2H shows a method 280 for managing editing to different versions of an image using a gain map, according to several embodiments. As shown in Figure 2H, method 280 begins in step 282, in which the computing device 102 accesses an enhanced image containing a high dynamic range (HDR) image and a gain map (for example, as described above in relation to Figure 2A). In step 284, the computing device 102 extracts the HDR image and gain map from the enhanced image (for example, as described above in relation to Figure 2B). In step 286, the computing device 102 generates a standard dynamic range (SDR) image using the HDR image and gain map (for example, as described above in relation to Figure 2C).

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

[0050] Furthermore, it should be noted that under alternative methods, if the computing device 102 determines that the image correction command 242 applied to the multichannel HDR image 215 can be modified to apply to the multichannel gain map 217, the generation of the multichannel SDR image 232 (described above in relation to Figure 2C) may be omitted. In particular, the multichannel gain map 217 can be modified to generate a modified multichannel gain map 217, and when the modified multichannel gain map 217 is applied to the multichannel HDR image 215, it generates the multichannel SDR image 232 as if the multichannel SDR image 232 had been modified using the technique described above in relation to step 250 in Figure 2E. This method can improve the overall efficiency of the computing device 102 in executing image correction commands by eliminating redundant modifications to the multichannel SDR image 232, as well as subsequent gain map regeneration operations.

[0051] Figures 3A to 3F are a series of conceptual diagrams illustrating techniques for utilizing gain maps to manage the output of an image on a display device, according to several embodiments. As shown in Figure 3A, step 310 may include a computing device 102 receiving an enhanced multichannel image 312 consisting of pixels 314. In particular, as in the scenario described above in relation to Figure 2A, pixels 314 include interleaved pixels 316 (each indicated as "P") of a first version of the multichannel image, and interleaved pixels 318 (each indicated as "P'") of a multichannel gain map. In this regard, the enhanced multichannel image 312 includes information from both the first version of the multichannel image and the multichannel gain map. Again, it should be noted that the embedding technique shown in Figure 3A is not intended to be limiting, and information from the first version of the multichannel image and the multichannel gain map can be incorporated into the enhanced multichannel image 312 using any conceivable technique without departing from the scope of this disclosure.

[0052] Figure 3B shows step 320, in which the computing device 102 extracts a first version of the multichannel image (shown as multichannel image 315) and a multichannel gain map (shown as multichannel gain map 317) from the enhanced multichannel image 312. This extraction can be performed using the same or similar techniques described above in relation to Figure 2B. In either case, at the end of step 320, the computing device 102 has placed both the multichannel image 315 and the multichannel 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] Figure 3C illustrates step 330, in which the computing device 102 identifies a headroom level 334 for a second version of an image based on the current brightness setting 333 of a display device 332 (communically coupled to the computing device 102). According to some embodiments, the current brightness setting 333 of the display device 332 can affect the color / luminosity dynamic range that the display device 332 can accurately display for human perception. In particular, as the brightness setting of the display device increases, the color / luminosity dynamic range that can accurately be output by the display device 332 decreases, while as the brightness setting of the display device decreases, the color / luminosity dynamic range that can accurately be output by the display device 332 increases. In this regard, scaling the color / luminosity range of a given image may be beneficial, which can be done using the aforementioned headroom level 334 according to the current brightness of the display device. This technique offers various benefits in that the display device is not obligated to display an image with color / luminosity outside the current range that the display device can display.

[0054] Without departing from the scope of this 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 for the display device 332 (e.g., detectable using one or more light sensors) (which, like the current luminance setting 333 of the display device 332, can affect the color / luminosity that the display device 332 outputs and which can be 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, wear level information (i.e., a pixel level usage map) may indicate that certain pixels of the display device 332 are moving more frequently than other pixels of the display device 332, thereby preventing them from accurately displaying color / luminosity. Note that the above examples are not intended to limit, and without departing from the scope of this disclosure, the headroom level 334 can be established at any level of granularity using any information that affects the ability of the display device 332 to accurately display color / luminosity.

[0055] According to some embodiments, the headroom level 334 represents a single value (e.g., a weight) applied to the multichannel gain map 317 before generating a second version of the multichannel image using the multichannel gain map 317 (details of which are described below in conjunction with Figure 3D). Under another technique, the headroom level 334 can take the form of a set of weights that are applied correspondingly to each of the multichannel gain maps 317. This technique could include, for example, individual weights for each pixel in the enhanced multichannel image 312 (in a 1:1 ratio), individual weights for every two pixels in the enhanced multichannel image 312 (in a 1:2 ratio), or individual weights for every N pixels in the enhanced multichannel image 312 (in a 1:N ratio). Again, the above examples are not limiting, and it should be noted that the headroom level 334 can take any form of modifying the multichannel 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 the computing device 102 establishing a modified multi-channel gain map 336 (including pixel 337) based on the headroom level 334. As shown in Figure 3C, pixel 337 of the multi-channel gain map 317 is indicated with "P''" to indicate that it is modified relative to pixel 318 of the multi-channel gain map 336, which is indicated with "P'".

[0057] Figure 3D shows step 340, in which the computing device 102 generates a second version of the multichannel image by performing a multiplication operation 341 that includes a first version of the multichannel image (i.e., multichannel image 315) and a modified multichannel gain map 336. As shown in Figure 3D, the above generation of the modified multichannel gain map 336 can be performed using a technique similar to that described above in relation to Figure 2C. In either case, the generation results in a second version of the multichannel image (illustrated in Figure 3D as multichannel image 342 (including pixels 343)) that can be output on the display device 332. Thus, Figure 3E shows step 350, in which the computing device 102 displays the second version of the multichannel image (i.e., multichannel image 342) on the display device 332. In this regard, multichannel image 342 represents a modified version of multichannel image 315 optimized for display on the display device 332 based on the headroom level 334 described above in relation to Figure 3C.

[0058] In addition, Figure 3F shows a method 360 for utilizing gain maps to manage the output of an image on a display device, according to several embodiments. As shown in Figure 3F, the method 360 begins in step 362, in which the computing device 102 accesses an enhanced image containing a first version of the image and a plurality of gain maps. In step 362, the computing device 102 identifies the headroom level of a second version of the image (for example, as described above with respect to Figure 3C) based on the current brightness setting of the display device. In step 364, the computing device 102 identifies a specific gain map from the plurality of gain maps that corresponds to the headroom level. In step 366, the computing device 102 generates a second version of the image using the first version of the image and the specific gain map. In step 368, the computing device 102 displays the second version of the image on the display device (for example, as described above in conjunction with Figure 3E).

[0059] Furthermore, it should be noted that an enhanced multichannel image may include multiple gain maps spanning a range of luminances that can be represented by the display device. For example, if a given display device can display 20 different luminance levels, the enhanced multichannel image may include 20 different gain maps, each corresponding to one of the 20 distinct luminance levels. In this regard, the gain map modification operation described above in relation to Figures 3A to 3F can be replaced by a simple lookup (and application) of the appropriate gain map corresponding to the current luminance level. This technique can increase the overall speed at which the baseline multichannel image in the enhanced multichannel image can be adjusted for output on the display device at its current luminance level. Furthermore, it should be noted that the multiple gain maps may be based on other display factors described herein, including external lighting conditions for the display. This may include, for example, identifying the appropriate gain map based on the current luminance level of the display, and then modifying the appropriate gain map based on the external lighting conditions for the display (or vice versa). The aforementioned methods are not intended to be limiting, and it should be noted that, without departing from the scope of this disclosure, enhanced multichannel images may include any number of gain maps based on any number of factors affecting the display output capability.

[0060] Figures 4A to 4F 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 a gain map, according to several embodiments. As shown in Figure 4A, step 410 includes the computing device 102 accessing a multi-channel HDR image 411 (including pixels 412 and subpixels 414 as described herein). This may include, for example, the computing device 102 receiving a request to import the multi-channel HDR image 411 into a photo library managed by the computing device 102 and accessible to the user of the computing device 102. This may occur, for example, when the user is importing HDR images from an advanced digital camera (with HDR capabilities), or when the user is receiving HDR images from someone else. Under these scenarios, it may be desirable to be able to accurately display the SDR version of the HDR image when appropriate, especially if the display device communicably coupled with the computing device 102 can only display the color / luminosity of the SDR image. This can also be desirable when HDR and SDR images are displayed as thumbnails between each other, typically causing the user to see the HDR image as too bright, while the SDR image appears too dark (even when displayed correctly on an HDR-enabled display). In this scenario, the computing device 102 uses a gain map to reduce the HDR image (partially or entirely) to a range that matches the SDR image (and / or vice versa) in order to balance the overall intensity of the thumbnails.

[0061] Accordingly, Figure 4B shows step 420, which includes the computing device 102 generating a multichannel SDR image 422 (including pixels 423) by applying a global tone mapping operation 421 to a multichannel HDR image 411. Here, generation is necessary if the multichannel HDR image 411, unlike the enhanced multichannel images described herein, does not (yet) include a multichannel gain map that enables the generation of a corresponding multichannel SDR image. However, as described herein, the global tone mapping operation 421 may be used to generate an approximation of the corresponding multichannel SDR image. In particular, the global tone mapping operation may include mapping an extended HDR color range to a more limited SDR color range, with efforts to reduce the introduction of artifacts (such as banding with reduced bit depth that reduces the granularity in which gradient transitions may be visible). Note that any alternative (or additional) image-based processing / modification may be applied to the multichannel HDR image 411 without departing from the scope of this disclosure.

[0062] In either case, Figure 4C shows step 430, which includes the computing device 102 generating a multichannel gain map 434 (including pixels 435) by performing a comparison 432 between the multichannel HDR image 411 and the multichannel SDR image 422. The comparison 432 can be performed using the same or similar techniques described above in relation to Figure 2F (in particular, the first method which involves dividing the value of each pixel in the multichannel SDR image 422 by the value of the corresponding pixel in the multichannel HDR image 411 to generate a quotient).

[0063] Next, Figure 4D shows step 440, in which the computing device 102 embeds the multichannel gain map 434 into the multichannel HDR image 411. Using the same or similar techniques described above in relation to Figure 2G, step 440 can be performed, as shown in Figure 4D, in which information about the pixels 435 of the multichannel gain map 434 is injected into the multichannel HDR image 411 (e.g., adjacent pixel information, extended channel information, additional metadata information, separate image information, etc.). At this point, the multichannel HDR image 411 effectively transitions to an enhanced multichannel image 122, which includes the multichannel HDR image 411 and the multichannel gain map 434. Furthermore, since the multichannel SDR image 422 can be reconstructed using the multichannel HDR image 411 and the multichannel gain map 434, there is no need to retain the multichannel SDR image 422. Therefore, Figure 4E shows step 450, in which the computing device 102 discards the multichannel SDR image 422.

[0064] Furthermore, Figure 4F shows a method 460 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 a gain map, according to several embodiments. As shown in Figure 4F, method 460 begins in step 462, in which the computing device 102 accesses the high dynamic range (HDR) image (for example, as described above in relation to Figure 4A). In step 464, the computing device 102 generates a standard dynamic range (SDR) image by applying a global tone mapping operation to the HDR image (for example, as described above in relation to Figure 4B).

[0065] In step 466, the computing device 102 generates a gain map by comparing the SDR image with the HDR image (for example, as described above in relation to Figure 4C). In step 468, the computing device 102 embeds the gain map into the HDR image (for example, as described above in relation to Figure 4D). In step 470, the computing device 102 receives a request to view the SDR version of the HDR image. In 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 shows a detail diagram of a computing device 500 that can be used to perform various techniques described herein, according to several embodiments. In particular, the detail diagram shows various components that may be included in the computing device 102 described in relation to Figure 1. As shown in Figure 5, the computing device 500 may include a processor 502 representing 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 can take various forms, such as inputs in the form of buttons, keypads, dials, touchscreens, audio input interfaces, visual / image capture input interfaces, sensor data, etc. Furthermore, the computing device 500 may include a display 510 that can be controlled by the processor 502 (e.g., via graphics components) to display information to the user. A data bus 516 can facilitate data transfer between at least the storage device 540 and the processor 502 and the controller 513. The controller 513 can interface with and control different devices through the device control bus 514. The computing device 500 may also include a network / bus interface 511 coupled to the 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 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, and the like. The computing device 500 may also include random access memory (RAM) 520 and 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 a volatile data storage device which stores instructions related to the operation of an application running on the computing device 500, for example, an image analyzer 110 / gain map generator 120.

[0068] The techniques described herein include a first technique for utilizing a gain map to manage editing for different versions of an image. According to some embodiments, the first technique may be performed by a computing device and includes the steps of: (1) accessing an enhanced image including a high dynamic range (HDR) image and a gain map; (2) extracting the HDR image and a gain map from the enhanced image; (3) generating a standard dynamic range (SDR) image using the HDR image and a gain map; (4) receiving and applying a first modification instruction to the HDR image; (5) generating a second modification instruction based on at least 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 on at least a first modification instruction includes (1) identifying at least one change to an HDR image caused by applying the first modification instruction, and (2) determining how to apply at least one complementary change to an SDR image, the second modification instruction, when applied to an SDR image, causes at least one complementary change to the SDR image.

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

[0071] According to some embodiments, comparing an HDR image with an 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 a second gain map. According to some embodiments, the second gain map is embedded in the SDR 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 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 utilizing multiple gain maps to manage the output of an image on a display device. According to some embodiments, the second technique may be performed by a computing device and includes the steps of: (1) accessing an enhanced image including a first version of the image and multiple gain maps; (2) identifying a headroom level for a second version of the image based on the current brightness setting of the display device; (3) identifying a specific gain map from among the multiple gain maps that corresponds to the headroom level; (4) generating a second version of the image using the first version of the image and the specific 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 the external lighting conditions for the display device. According to some embodiments, the external lighting conditions are detected using at least one light sensor communicatively coupled to a computing device. According to some embodiments, the headroom level scales inversely to the current brightness setting. According to some embodiments, a second version of the image is output precisely 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 the generation of 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 may be performed by a computing device and includes the steps of (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 into the HDR image, (5) receiving a request to view an SDR version of the HDR image, and (6) providing an SDR version of the HDR image using the HDR image and the gain map.

[0075] According to some embodiments, global tone mapping operation reduces the bit depth of each pixel in an HDR image. According to some embodiments, comparing an SDR image with an HDR image includes, for each pixel in 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 in a gain map as the corresponding pixel. According to some embodiments, embedding a gain map in an HDR image includes, for each pixel in 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 a gain map in an HDR image includes storing the gain map as metadata associated with the HDR image.

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

[0077] The various aspects, embodiments, implementations, or features of the described embodiments can be used individually or in any combination. The various aspects of the described embodiments can be implemented in software, hardware, or a combination of hardware and software. The described embodiments can also be implemented as computer-readable code on a computer-readable medium. This computer-readable medium is any data storage device capable of storing data that can later be read by a computer system. Examples of computer-readable media include read-only memory, random-access memory, CD-ROMs, DVDs, magnetic tapes, hard disk drives, solid-state drives, and optical data storage devices. The computer-readable medium can also be distributed across a network of computer systems so that the computer-readable code is stored and executed in a distributed manner.

[0078] In the preceding description, certain technical terms have been used for illustrative purposes to provide a complete understanding of the described embodiments. However, it will be apparent to those skilled in the art that specific details are not required to put the described embodiments into practice. Therefore, the descriptions of the specific embodiments above are provided for illustrative and explanatory purposes only. They are not intended to be exhaustive or to limit the described embodiments to the exact form disclosed. It will be apparent to those skilled in the art that many modifications and variations are possible in light of the teachings above.

Claims

1. A method for utilizing a first gain map to manage editing for different versions of an image, wherein the method is performed on a computing device, Accessing a high dynamic range (HDR) image and an enhanced image including the first gain map, Extracting the HDR image and the first gain map from the enhanced image, A standard dynamic range (SDR) image is generated using the HDR image and the first gain map. The process involves receiving and applying a first modification command to the aforementioned HDR image, At least the first modification instruction is used to generate a second modification instruction, Applying the second correction command to the SDR image, After applying the first and second correction instructions, a second gain map is generated by comparing the HDR image with the SDR image, or vice versa. After applying the first and second correction instructions, the second gain map is embedded in the HDR image or the SDR image. Methods that include...

2. The method according to claim 1, wherein embedding the second gain map in the HDR image includes storing metadata indicating the second gain map in the HDR image.

3. The method according to claim 1, wherein embedding the second gain map into the HDR image includes interleaving a given pixel of the second gain map between two pixels of the HDR image.

4. The method according to claim 1, wherein embedding the second gain map into the HDR image includes embedding specific pixels of the second gain map into corresponding pixels of the HDR image as additional channels for the corresponding pixels.

5. The method according to claim 1, wherein applying the first modification command to the HDR image includes applying a markup to the HDR image.

6. The method according to claim 1, wherein applying the first modification command to the HDR image includes applying a filter to the HDR image.

7. A non-temporary computer-readable storage medium configured to store instructions, wherein, when an instruction is executed by at least one processor included in a computing device, the computing device is: Accessing an enhanced image including a high dynamic range (HDR) image and a first gain map, Extracting the HDR image and the first gain map from the enhanced image, A standard dynamic range (SDR) image is generated using the HDR image and the first gain map. The process involves receiving and applying a first modification command to the aforementioned HDR image, At least the first modification instruction is used to generate a second modification instruction, Applying the second correction command to the SDR image, After applying the first and second correction instructions, a second gain map is generated by comparing the HDR image with the SDR image, or vice versa. A non-temporary computer-readable storage medium that allows the first gain map to be used to manage editing for different versions of an image by performing a step that includes embedding the second gain map into the HDR image or the SDR image after applying the first and second modification instructions.

8. The non-temporary computer-readable storage medium according to claim 7, wherein embedding the second gain map in the HDR image includes storing metadata indicating the second gain map in the HDR image.

9. The non-temporary computer-readable storage medium according to claim 7, wherein embedding the second gain map into the HDR image comprises interleaving a given pixel of the second gain map between two pixels of the HDR image.

10. The non-temporary computer-readable storage medium according to claim 7, wherein embedding the second gain map into the HDR image includes embedding specific pixels of the second gain map into corresponding pixels of the HDR image as additional channels of the corresponding pixels.

11. The non-temporary computer-readable storage medium according to claim 7, wherein applying the first modification instruction to the HDR image includes applying a markup to the HDR image.

12. The non-temporary computer-readable storage medium according to claim 7, wherein applying the first modification instruction to the HDR image includes applying a filter to the HDR image.

13. The non-temporary computer-readable storage medium according to claim 7, wherein generating the second correction instruction includes adjusting the first correction instruction based on the difference between the HDR image and the SDR image.

14. A computing device configured to manage editing for different versions of an image using a first gain map, wherein the computing device At least one processor, The computing device comprises at least one memory for storing instructions, and when an instruction is executed by the at least one processor, it is transmitted to the computing device. Accessing a high dynamic range (HDR) image and an enhanced image including the first gain map, Extracting the HDR image and the first gain map from the enhanced image, A standard dynamic range (SDR) image is generated using the HDR image and the first gain map. The process involves receiving and applying a first modification command to the aforementioned HDR image, At least the first modification instruction is used to generate a second modification instruction, Applying the second correction command to the SDR image, After applying the first and second correction instructions, a second gain map is generated by comparing the HDR image with the SDR image, or vice versa. A computing device that performs the step of embedding the second gain map into the HDR image or the SDR image after applying the first and second modification instructions.

15. The computing device according to claim 14, wherein embedding the second gain map in the HDR image includes storing metadata indicating the second gain map in the HDR image.

16. The computing device according to claim 14, wherein embedding the second gain map into the HDR image includes interleaving a given pixel of the second gain map between two pixels of the HDR image.

17. The computing device according to claim 14, wherein embedding the second gain map into the HDR image includes embedding specific pixels of the second gain map into corresponding pixels of the HDR image as additional channels of the corresponding pixels.

18. The computing device according to claim 14, wherein applying the first modification instruction to the HDR image includes applying a markup to the HDR image.

19. The computing device according to claim 14, wherein applying the first modification instruction to the HDR image includes applying a filter to the HDR image.

20. The computing device according to claim 14, wherein generating the second correction instruction includes adjusting the first correction instruction based on the difference between the HDR image and the SDR image.

Images