High dynamic range digital image editing visualization

Abstract

The embodiment of the invention relates to high dynamic range digital image editing visualization. A high dynamic range editing system is configured to generate a visualization to assist in digital image editing in both a high dynamic range and a standard dynamic range. In a first example, a visualization is generated as a histogram. In a second example, a visualization is generated to indicate the high dynamic range capability. In a third example, a visualization is generated to indicate a range of luminance values within the digital image. In a fourth example, the visualization is generated as a point curve that defines a mapping between luminance values detected from the digital image over both a standard dynamic range and a high dynamic range and output luminance values. In a fifth example, the visualization is generated as a preview to convert pixels in the digital image that are in a high dynamic range to a standard dynamic range.

Description

Background Art

[0001] High dynamic range (HDR) as applied to digital images refers to brightness calculations (i.e., lighting) performed in a high dynamic range that supports a greater range of values ​​than are available in a standard dynamic range (SDR). By using high dynamic range capabilities, bright objects in a digital image appear brighter, dark objects appear darker, and visibility of details in the digital image is increased when displayed by a display device that would otherwise be lost due to the limitations of contrast in a conventional standard dynamic range.

[0002] However, conventional techniques for achieving high dynamic range capabilities by display devices vary between display devices and the implementations used to support those display devices. This variation can lead to inconsistencies in real-world scenes and reduced functionality when tasked with editing these digital images. Summary of the invention

[0003] A high dynamic range editing system is configured to generate visualizations to assist in digital image editing in both high dynamic range and standard dynamic range. The visualization can be configured in various ways for display in a user interface to address challenges in digital image editing involving high dynamic range. In a first example, the visualization is generated as a histogram. In a second example, the visualization is generated to indicate high dynamic range capabilities, for example, as detected for a particular display device or received as user input to define a target display device. In a third example, the visualization is generated to indicate the range of brightness values ​​within a digital image. In a fourth example, the visualization is generated as a point curve that defines a mapping between brightness values ​​detected from a digital image and output brightness values ​​on both a standard dynamic range and a high dynamic range. In a fifth example, the visualization is generated as a preview to convert pixels in a digital image that are in a high dynamic range to a standard dynamic range.

[0004] This Summary introduces a selection of concepts in a simplified form that are further described below in the Detailed Description. As such, this Summary is not intended to identify essential features of the claimed subject matter, nor is it intended to be used as an aid in determining the scope of the claimed subject matter. BRIEF DESCRIPTION OF THE DRAWINGS

[0005] The patent or application file contains at least one drawing executed in color. Copies of this patent or patent application publication with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0006] The detailed description is described with reference to the accompanying drawings. The entities represented in the drawings refer to one or more entities, and thus singular or plural forms of the entities may be referred to interchangeably in the discussion.

[0007] Figure 1 is an illustration of a digital media environment in an example implementation for employing high dynamic range digital image editing visualization of a high dynamic range digital image as described herein.

[0008] Figure 2 Depicted in more detail Figure 1 The system is provided in an example implementation of an HDR editing system and an operation of a visualization generation module.

[0009] Figure 3 Depicted in more detail is shown by Figure 2 An example implementation of the histogram generation module for generating a histogram.

[0010] Figure 4 is a flow chart depicting a step-by-step procedure in an example implementation of operations that may be performed by a processing device to arrive at a result of generating a visualization as a histogram configured to aid in editing of a digital image.

[0011] Figure 5 Depicted in more detail is shown by Figure 2 An example implementation of a capacity visualization module that generates a visualization of display capacity with respect to a histogram.

[0012] Figure 6 Depicted are example implementations of visualizations and histograms illustrating differences in headroom in supported luminance values ​​in a high dynamic range for a display device based on ambient conditions.

[0013] Figure 7 Depicted in more detail is shown by Figure 2 The capability visualization module generates an example implementation of a visualization showing capabilities as an overlay.

[0014] Figure 8 Depicted in more detail is shown by Figure 2 An example implementation of a capability visualization module that generates a visualization of display capabilities as color codes associated with numerical values ​​of corresponding color channels of pixels.

[0015] Fig. 9 is a flow chart depicting a step-by-step procedure in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization indicative of high dynamic range capability.

[0016] Fig.10 Depicted in more detail is shown by Figure 2 An example implementation of the range visualization module for generating visualizations.

[0017] Fig.11is a flow chart depicting a step-by-step procedure in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization indicating a range of luminance values ​​within a high dynamic range, the visualization being configured to assist in editing of a digital image.

[0018] Fig.12 Depicted in more detail is shown by Figure 2 The point-curve visualization module generates an example implementation of a visualization as point-curves.

[0019] Fig.13 is a flow chart depicting a step-by-step procedure in an example implementation of operations that may be performed by a processing device to arrive at a result of generating a visualization as a point curve as a mapping between luminance values ​​detected from a digital image and output luminance values ​​over a standard dynamic range and a high dynamic range.

[0020] Fig.14 Depicted in more detail is shown by Figure 2 An example implementation of a preview visualization module that generates a visualization as a standard dynamic range preview of a digital image, the standard dynamic range preview being configured for output in a high dynamic range.

[0021] Fig.15 is a flow chart describing a step-by-step procedure in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization as a standard dynamic range preview of a high dynamic range digital image.

[0022] Fig.16 An example system is shown that includes various components of an example device that can be implemented as a reference Figures 1 to 15 Any type of computing device described and / or used to implement embodiments of the techniques described herein. DETAILED DESCRIPTION

[0023] Overview

[0024] High dynamic range (HDR) has been developed to support an increased range of brightness values ​​as part of rendering a digital image for display on a display device. However, display devices in real-world scenarios vary in the amount and type of HDR capabilities (e.g., the range of brightness values ​​supported) available for displaying digital images.

[0025] In addition, environmental conditions can also affect the HDR capabilities of these display devices. For example, a wider range of brightness values ​​is typically available in shaded conditions, even for the same display device, compared to the range of brightness values ​​available in bright conditions. Because of this, when faced with these challenges, conventional HDR technology lacks consistency in appearance, such as in color, hue, etc., across different display devices and in different environmental conditions. This results in reduced functionality, including reduced display range and accuracy of digital images, reduced contrast, etc.

[0026] Furthermore, these challenges also directly impact the functionality available for editing digital images. For example, a display device used by a content editor may have different capabilities for displaying HDR-enabled digital images than a display device used by an end consumer. For example, even when the same display device is used, the environmental conditions at the respective display devices may be different, directly impacting the ability of these display devices to display portions of a digital image within a high dynamic range.

[0027] To address these and other technical challenges, a high dynamic range editing system is configured to generate visualizations to assist in digital image editing in both high dynamic range and standard dynamic range. The visualizations can be configured in various ways for display in a user interface to address challenges in digital image editing involving high dynamic range.

[0028] In a first example, the visualization is generated as a histogram. The histogram indicates the brightness distribution of brightness values ​​of at least one color channel over both the standard dynamic range and the high dynamic range, with respect to Figure 3 and Figure 4 Further discussion of this is described and illustrated.

[0029] In a second example, a visualization is generated to indicate high dynamic range capability, for example, as detected for a particular display device or received as user input defining a target display device. Examples of display capability visualizations include information about Figure 5 An indication of supported and unsupported ranges of the histogram shown, such as Figure 6 The difference in clearance of the same display device due to changes in environmental conditions is shown in Figure 7 The superposition shown, and Figure 8 The illustrated use of display characteristics (eg, color coding) to indicate support or lack of support for values ​​in different color channels for a selected pixel.

[0030] In a third example, a visualization is generated to indicate a range of brightness values ​​within a digital image. A visualization characteristic (e.g., color coding) is used to indicate pixels included within a corresponding range of brightness values, e.g., for intervals within a high dynamic range. Fig.10 and Fig.11A further discussion of the third example is described and illustrated.

[0031] In a fourth example, a visualization is generated as a point curve that defines a mapping between luminance values ​​detected from a digital image and output luminance values ​​over both a standard dynamic range and a high dynamic range. For example, the point curve can be used to adjust the mapping, and therefore output luminance values, as part of generating an edited digital image. In an implementation, luminance values ​​in the standard dynamic range are indicated in the point curve using a first scale (e.g., a linear scale), and luminance values ​​in a high dynamic range (HDR) are indicated in the point curve using a second scale different from the first scale (e.g., a logarithmic scale). Fig.12 and Fig.13 A further discussion of the third example is described and illustrated.

[0032] In a fifth example, a visualization is generated as a preview to convert pixels in a digital image that are in a high dynamic range to a standard dynamic range. In this way, an insight is provided into how a digital image that supports a high dynamic range will look when displayed in a standard dynamic range. Fig.14 and Fig.15 Further discussion of the fifth example is described.

[0033] In the following discussion, an example environment is described that employs the techniques described herein. Example programs that can be executed in the example environment and other environments are also described. Therefore, execution of the example programs is not limited to the example environment, and the example environment is not limited to execution of the example programs.

[0034] Sample HDR image editing environment

[0035] Figure 1 1 is an illustration of a digital media environment 100 in an example implementation for employing high dynamic range digital image editing visualization of a high dynamic range digital image as described herein. The illustrated environment 100 includes a computing device 102, which can be configured in a variety of ways.

[0036] For example, computing device 102 may be configured as a desktop computer, a laptop computer, a mobile device (e.g., assuming a handheld configuration, such as a tablet or mobile phone as shown), etc. Thus, computing device 102 ranges from full-resource devices with large amounts of memory and processor resources (e.g., personal computers, game consoles) to low-resource devices with limited memory and / or processing resources (e.g., mobile devices). Furthermore, although a single computing device 102 is shown, computing device 102 is representative of a plurality of different devices, such as Fig.16 Multiple servers used by an enterprise to perform "on-cloud" operations as described in .

[0037] The display device 104 is communicatively coupled 106 to the computing device 102, for example, via a wired connection or a wireless connection. The display device 104 includes a display module 108 that represents functionality for displaying digital images (e.g., still digital images), digital videos, digital documents, etc. The display device 104 and display module 108 may be configured in various ways to incorporate various display technologies, examples of which include light emitting diodes (LEDs), organic light emitting diodes (OLEDs), projectors, etc.

[0038] In the illustrated example, the display module 108 includes support for high dynamic range (HDR) functionality, which is represented as HDR display module 110. High dynamic range (HDR) applied to digital images refers to brightness calculations (i.e., lighting) performed within a high dynamic range that supports a greater range of values ​​than are available in a standard dynamic range (SDR). By using high dynamic range functionality, bright objects in a digital image appear brighter, dark objects appear darker, and visibility of details is increased that would otherwise be lost due to contrast limitations.

[0039] The ability of the HDR display module 110 to support HDR capabilities 112 depends on various capabilities, examples of which include hardware device capabilities 114, software capabilities 116, and environmental capabilities 118. Hardware device capabilities 114 depend on the ability of the display device 104 hardware to support a range of brightness values, such as "how bright" and "how dark" to activate a pixel. Software capabilities 116 refer to the ability of the display device 104 to process digital images to achieve this function through the hardware device, such as support for associated drivers, etc. Environmental capabilities 118 depend on the environmental conditions of the environment in which the display device 104 is located, for example, lighting conditions such as "how bright" and "how dark", glare, etc.

[0040] Computing device 102 implements HDR editing system 120 to edit digital image 122, which is shown stored in storage device 124. For example, digital image 122 includes a plurality of pixels 126 supporting a standard dynamic range 128 (SDR) and a high dynamic range 130 (HDR) of luminance values.

[0041] The term "dynamic range" refers to the contrast between the lightest and darkest tones in a digital image, which can be measured in "f-stops" that describe the relative amounts of light. For example, a digital image with less than four f-stops of dynamic range is generally considered to be low contrast (i.e., low dynamic range), while a digital image with eight or more f-stops is considered to be high contrast or have a high dynamic range (HDR). Brightness refers to the amount of light shining in a particular direction, and is usually measured in candela per square meter and is also referred to as "nits."

[0042] For example, the digital image shown on the display device 104 includes different amounts of light in different corresponding parts, from a maximum value of 132 nits and highlights 134 (e.g., 4000 nits) at the sun to a midtone 136 (e.g., 1000 nits) and a decreasing value to a shadow 138 (e.g., 100 nits). The display device also uses nits to quantify brightness. In the past, the typical maximum brightness of a display device was about 250 nits. In some current examples, mobile phones and tablets support 1000 nits on the entire screen, and the peak brightness is as high as 1600 nits. In addition, the display device can be configured to implement various technologies to maintain deep black and improve contrast by using local dimming, using organic light emitting diodes (OLEDs), etc. Compared with the standard dynamic range supported by conventional display devices, these display devices are called "HDR displays" due to the ability to achieve a high peak with deep black to provide an increased contrast range.

[0043] For example, the standard dynamic range of 128 is limited to the standard brightness range of the user interface. Therefore, the brightness of a digital image configured according to the standard dynamic range (SDR) cannot be greater than SDR white, which is the maximum white commonly used for text, icons, menus, and other interface elements. In other words, the brightness in the user interface is limited to SDR white similar to the limitation that a photo printed on physical paper cannot be brighter than the paper itself.

[0044] On the other hand, with high dynamic range 130, tones can be brighter than SDR white and support a high dynamic range, for example, from the shadows 138 of the mountains shown to the maximum 132 of the sun. Thus, HDR capability 112 provides, in practice, an additional two to four f-stops of highlight headroom compared to conventional display devices limited to standard dynamic range. Thus, tones and colors have additional room to "expand" to support brighter highlights, deeper shadows, improved tonal separation, and vivid colors. As a result, digital images 122 supporting high dynamic range 130 for display using HDR capability 112 of display device 104 have increased impact and support an increased sense of depth and realism.

[0045] However, conventional techniques for editing digital images 122 face many technical challenges when the digital images 122 have a high dynamic range 130. For example, the technical challenges include the ability to view the high dynamic range 130 based on the HDR capability 112 at the display device 104, and challenges when the edited digital image is to be viewed by other display devices having other HDR capabilities (e.g., hardware device capabilities, software capabilities, and environmental capabilities).

[0046] To address these technical challenges, visualization generation module 140 is used to generate visualizations that can be displayed in a user interface as an aid to editing digital images 122 and viewing the effects of these edits. Thus, the techniques described herein improve device operation, increase data storage efficiency, and improve digital image 122 editing techniques to address different device and environment capabilities.

[0047] Further discussion of these examples and other examples is included in the following sections and is shown in the corresponding figures. Typically, the functions, features, and concepts described with respect to the examples above and below are employed in the context of the example programs described in this section. In addition, the functions, features, and concepts described with respect to the different figures and examples in this document are interchangeable with each other and are not limited to being implemented in the context of a particular figure or program. In addition, the boxes associated with the different representative programs and corresponding figures herein may be applied together and / or may be combined in different ways. Therefore, the various functions, features, and concepts described with respect to the different example environments, devices, components, figures, and programs herein may be used in any suitable combination and are not limited to the specific combinations represented by the examples listed in this specification.

[0048] High Dynamic Range Digital Image Editing Visualization

[0049] The following discussion describes high dynamic range digital image editing visualization techniques that can be implemented using the previously described systems and devices. Aspects of each program are implemented in hardware, firmware, software, or a combination thereof. The programs are shown as a set of blocks that specify operations performed by one or more devices, and are not necessarily limited to the order shown for performing the operations by the corresponding blocks.

[0050] Figure 2 Depicted in more detail Figure 1 The system 200 in an example implementation of the operation of the HDR editing system and visualization generation module. Initially in this example, a digital image having pixels 126 in a standard dynamic range 128 and pixels 126 in a high dynamic range 130 is received 122 .

[0051] The HDR editing system 120 employs a brightness detection module 202 to detect a brightness value 204 for each pixel 126 in the digital image 122. For example, in a grayscale image, each pixel has a single value representing its brightness, e.g., in an eight-bit image, the value representing black is zero and the maximum value representing white is 255. For a digital image 122 having multiple color channels (e.g., RGB, HSV, CMYK, etc.), a brightness value 204 is detectable for each color channel. An overall brightness value may also be generated for the pixel as a whole, which may also take into account the sensitivity of the human eye to different color channels.

[0052] The brightness value 204 is then passed as input to the visualization generation module 140. The visualization generation module 140 generates a visualization 206 based on the brightness value 204, which is used by the image editing module 208 to support the creation of an edited digital image 210. For example, the image editing module 208 employs one or more operations 212 to change the color values ​​of the pixels 126 within the digital image within the standard dynamic range 128 and the high dynamic range 130, which is not possible in conventional techniques.

[0053] The visualization 206 can be configured in various ways. Therefore, the techniques that can be used to generate the visualization 206 can also be configured in various ways. Examples of functions that can be used to generate the visualization 206 are represented as a histogram generation module 214, a capability visualization module 216, a range visualization module 218, a point curve visualization module 220, and a preview visualization module 222.

[0054] The histogram generation module 214 is configurable to generate the visualization 206 as a histogram. The histogram indicates the brightness distribution of brightness values ​​of at least one color channel over the standard dynamic range 128 and the high dynamic range 130, with respect to Figure 3 and Figure 4 Further discussion of this is described and illustrated.

[0055] The capability visualization module 216 is configured to generate the visualization 206 to indicate HDR capabilities. For example, the capability input module 224 generates data 226 describing HDR capabilities 228, which is used as a basis for forming the visualization 206 to indicate capabilities. In a first example, the capability input module 224 detects the HDR capabilities 112 of a particular display device 104, which may include hardware device capabilities 114, software capabilities 116, and / or environment capabilities 118 as previously described. In another example, the capability input module 224 is provided as user input via a user interface, for example, so that editing of the digital image 122 is based on the HDR capabilities of the target device to render the edited digital image 210.

[0056] Examples of visualizations showing capabilities include Figure 5 An indication of supported and unsupported ranges of the histogram shown, such as Figure 6 The difference in clearance of the same display device due to changes in environmental conditions is shown in Figure 7 The superposition shown, Figure 8 As shown, the use of display characteristics (e.g., color coding) to indicate support or non-support of values ​​in different color channels of a selected pixel, etc., is also described with respect to Fig. 9 The procedure described in process 900.

[0057] The range visualization module 218 is configured to generate a visualization 206 to indicate a range of brightness values ​​within the digital image 122. As previously described, the histogram is configured to indicate a brightness distribution of brightness values ​​detected from the digital image 122, for example, as a relative number of pixels 126 in the digital image 122 for corresponding brightness values. The range visualization module 218 defines a range of brightness values. The ranges within the high dynamic range 130 of the histogram are associated with corresponding visualization characteristics, such as color coding. The color coding is then also applied to corresponding pixels within the digital image and thus directly indicates which pixels in the digital image are included in the corresponding range within the HDR, with respect to Fig.10 and Fig.11 Further discussion of this is described and illustrated.

[0058] The point curve visualization module 220 is configured to generate the visualization 206 as a point curve, which the image editing module 208 can then use through one or more operations 212 to perform editing, for example, adjusting a mapping and outputting brightness values ​​accordingly, as part of generating an edited digital image 210. The point curve defines a mapping between brightness values ​​204 detected from the digital image 122 and output brightness values ​​over both a standard dynamic range 128 and a high dynamic range 130. For example, the point curve can be used to adjust a mapping, and output brightness values ​​accordingly, as part of generating an edited digital image 210. The point curve overcomes conventional technical challenges by including both a standard dynamic range 128 and a high dynamic range 130, which is not possible in conventional techniques. About Fig.12 and Fig.13 Further discussion of the operation of the point curve visualization module 220 is described.

[0059] The preview visualization module 222 is configured to generate the visualization 206 as a preview to convert the pixels 126 in the high dynamic range 130 to the standard dynamic range 128. For example, the user input may be used to switch the user interface between a view of the digital image 122 displayed using the high dynamic range 130 and a view of the digital image 122 displayed using the standard dynamic range 128. In this manner, insight into how the high dynamic range 130 enabled digital image 122 would look in the standard dynamic range 128 is provided. Fig.14 and Fig.15 Further discussion of the operation of the point curve visualization module 220 is described.

[0060] Figure 3 Depicted in more detail is shown by Figure 2 An example implementation 300 of the histogram generation module 214 generating a histogram. Figure 44 is a flow chart depicting a step-by-step procedure 400 in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization as a histogram that is configured to assist in editing of a digital image. As previously described, the brightness detection module 202 is configured to detect brightness values ​​204 in the standard dynamic range 128 and the high dynamic range 130 from the digital image 122 (block 402).

[0061] The brightness value is then used by the histogram generation module 214 as a basis for generating a histogram 302 indicating a brightness distribution of brightness values ​​for at least one color channel. The brightness distribution indicates the relative number of pixels from the digital image having corresponding brightness values ​​in the standard dynamic range and the high dynamic range (box 404), which is displayed in the user interface (box 406).

[0062] For example, the histogram 302 includes a first axis (e.g., an X-axis) indicating luminance values ​​over a first portion corresponding to a standard dynamic range (SDR) 304 and a second portion corresponding to a high dynamic range (HDR) 306. A second axis (e.g., a Y-axis) is used to indicate a relative number of pixels from the digital image 122 having corresponding luminance values, which in the example shown is performed for corresponding ones of a plurality of color channels (e.g., a red channel, a green channel, and a blue channel) in an RGB color space.

[0063] The scale used to depict luma values ​​in the standard dynamic range 304 in the illustrated example is different than the scale used to depict luma values ​​in the high dynamic range 306. For example, the high dynamic range 306 includes a larger range of luma values ​​than the standard dynamic range 304. Therefore, in order to "fit these in," in this example, the standard dynamic range 304 uses a linear scale, while the high dynamic range 306 uses a logarithmic scale to indicate corresponding luma values.

[0064] For example, high dynamic range pixel values ​​are typically represented using a linear display. A pixel value of zero represents black, the minimum displayable value. A pixel value of one represents the SDR white level, the maximum displayable value for the user interface. A pixel value greater than one (e.g., "2.7") is "overrange," i.e., it is an HDR tone brighter than the SDR white level. This follows a linear scale because the pixel value is proportional to the energy of the display. As a specific example, a pixel value of "8.0" is eight times brighter than a pixel value of "1.0." In photographic terms, where the "log2" scale is often used, a pixel value of "8.0" is three f-stops brighter than a pixel value of "1.0" because "log2(8)=3."

[0065] Pixel values ​​represented using linear light are perceptually non-uniform. Therefore, user interface elements commonly found in image editing applications (e.g., histograms and dot curves) instead use "encoded" curves to map linear pixel values ​​into a perceptually uniform range. These curves are designed to utilize SDR data, where the SDR range is zero to one. Conventional examples include "sRGB," "Gamma 2.2," or Rec. "709," where linear image values ​​are mapped through a gamma function before being displayed as part of a histogram or dot curve.

[0066] However, conventional user interfaces do not support the inclusion of HDR values. Furthermore, the gamma functions described previously cannot naturally be extended to account for HDR values. For example, consider a linear set of values ​​from "0" to "16" (e.g., up to "+4" stops brighter than SDR white) mapped using a "gamma 2.2" curve. The maximum linear value of "16" is scaled via the "16 (1 / 2.2) ” mapping, which is approximately “3.5”. This means that visualizations such as histograms or dot curve interfaces that are typically confined within the “[0,1]” range of SDR will be expanded to “[0,3.5]” to support HDR data up to “+4” stops above SDR white. As a result, the HDR portion of the visualization (“1 to 3.5”) is significantly larger than the SDR portion of the visualization, which is awkward and inefficient in practice.

[0067] Therefore, in an implementation example, a hybrid sRGB-logarithmic curve is used as part of a visualization (e.g., histogram, point curve, etc.) that maps the linear range "[0,16]" to the encoded range "[0.1]", representing both the SDR and HDR parts. The function is represented as "f(x)", where "x" is the input of the linear display light (e.g., "1.0" represents SDR white). The function "f(x)" uses the sRGB curve to map the SDR range "[0,1]" to the range "[0,S]", where "s" is a configurable parameter, and uses the logarithmic curve to map the HDR range "[1,16]" to the region "[S,1]". The general form of the function "f" can be defined as three parts, examples of which are as follows:

[0068] f1(x,S) = x*12.92*S

[0069] ·f2(x,S) =S*(1.055*pow(x,1.0 / 2.4)-0.055)

[0070] f3(x,a,b,c)=a*log(x+b)+c

[0071] f(x,S,a,b,c)=f1(x,S) if (x<=0.0031308)

[0072] f2(x,S) if (x>0.0031308&&x

[0073] <=1.0)

[0074] f3(x,a,b,c) if (x>1.0)

[0075] The first two parts (i.e. "f1" and "f2") are the sRGB curve. The third part (f3) is a logarithmic curve.

[0076] In the example above, the constants "(a,b,c)" were chosen to satisfy these criteria:

[0077] "f3(1) = S". In other words, "f" maps the SDR white point to the parameter "S" to ensure the continuity of the function "f" satisfied by "f2" and "f3";

[0078] "f3(16)=1". In other words, "f" sets the linear HDR value to 16 (i.e. higher than SDR

[0079] The four levels of white) are mapped to 1; and

[0080] "f2'(1)=f3'(1)". In other words, when "x" is 1, the derivative of "f2" matches the derivative of "f3" to ensure the smoothness of the function "f" satisfied by "f2" and "f3".

[0081] The parameter "S" is chosen based on the desired balance between SDR and HDR in the coding space. For example, a value of "0.5" provides an equal balance between SDR and HDR. This means that coded values ​​in "[0,0.5]" represent SDR, and coded values ​​greater than "0.5" represent HDR.

[0082] Example values ​​for (S,a,b,c) in the implementation example include:

[0083] S = 255.0 / 500.0 = 0.51

[0084] a=0.15781

[0085] b = -0.296081

[0086] c = 0.565406

[0087] Various other examples are also contemplated.

[0088] The histogram 302 also includes an indication of SDR white 308 as the maximum brightness value supported by the standard dynamic range 304, as an indication of a transition between the standard dynamic range 304 and the high dynamic range 306. In this manner, the histogram 302 indicates that corresponding colors in the high dynamic range 306 are brighter than colors in the standard dynamic range 304.

[0089] The high dynamic range 306 in the histogram 302 is further divided into intervals defining respective ranges of brightness values, which double over successive intervals. To do this, in the illustrated example, the high dynamic range 306 is divided into f-stops, with indications at the first f-stop 310, the second f-stop 312, the third f-stop 314, and the fourth f-stop 316. As previously described, f-stops define respective amounts of brightness, which were originally defined in photography as being based on respective amounts of light allowed through a camera lens. Thus, in this example, successive intervals define respective amounts of brightness that double successively, for example, from the first f-stop 310 to the second f-stop 312, the third f-stop 314, and the fourth f-stop 316. Thus, the histogram 302 provides insight into the brightness of pixels within the digital image 122 within respective color channels, and the amount of those pixels having that brightness.

[0090] Figure 5 Depicted in more detail is shown by Figure 2 The capability visualization module 216 generates an example implementation 500 of a visualization showing capabilities with respect to a histogram. Figure 6 Depicted is an example implementation 600 of a visualization and histogram illustrating differences in the headroom in supported luminance values ​​in a high dynamic range of a display device based on ambient conditions. Figure 7 Depicted in more detail is shown by Figure 2 The capability visualization module 216 generates an example implementation 700 of displaying a visualization of a capability as an overlay. Figure 8 Depicted in more detail is shown by Figure 2 An example implementation 800 of the capability visualization module 216 generating a visualization of the display capabilities as color codes associated with numerical values ​​of corresponding color channels of pixels. Fig. 9 is a flow chart depicting a step-by-step procedure 900 in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization that is indicative of high dynamic range capability.

[0091] As previously mentioned Figure 2As described, the capability visualization module 216 is configured to receive input defining high dynamic range (HDR) capabilities (block 902). In a first example, the input is provided via a user interface. For example, a content creator may be tasked with creating a digital image for output by a particular display device, and may therefore manually specify HDR capabilities for that device. In a second example, the capability input module 224 detects in real time the HDR capabilities 228 of the associated display device 104, which may be based on hardware device capabilities 114, software capabilities 116, environmental capabilities 118, and the like.

[0092] As previously described, the luma detection module 202 detects luma values ​​204 of the digital image 122 in the standard dynamic range 128 and the high dynamic range 130 (block 904). A visualization is then generated that indicates which of the luma values ​​of the digital image 122 are supported by the HDR capability and which of the luma values ​​are not supported by the HDR capability (block 906).

[0093] For example, Figure 5 The visualization includes Figure 3 302 and a display capability visualization 502 indicating a supported range 504 within the high dynamic range 306 and an unsupported range 506 within the high dynamic range 306. To this end, in this example, a first visualization indication 508 is employed, which uses a first visualization characteristic (e.g., as a color coding) on ​​a range of brightness values ​​having the high dynamic range 306, which shows corresponding values ​​included in the supported range 504, for example, by a yellow bar next to the corresponding brightness value.

[0094] A second visual indication 510 is also employed that uses a second visual characteristic (e.g., also as color coding in this example) over the range of luminance values ​​having the high dynamic range 306, which shows corresponding values ​​in the unsupported range 506, e.g., by a red bar next to the corresponding luminance value. Thus, in this example, the first visual indication 508 indicates the amount of “headroom” available for displaying the digital image 122 in the high dynamic range 130. As previously described, this headroom amount can change based on changes in the hardware device capabilities 114 and software capabilities 116 and even environmental capabilities 118 of the same display device, examples of which are described below.

[0095] Figure 6An example implementation 600 of a visualization and histogram is depicted that illustrates the difference in headroom in supported brightness values ​​of a display device in a high dynamic range based on environmental conditions. In a first example 602, a histogram with a first visual indication 604 is shown that indicates the amount of "headroom" (i.e., the range of luminosity values) available in a high dynamic range 130 in a bright environment. Because the environment is bright in this example, the range available for displaying a digital image 122 is reduced due to an increase in the amount of backlight. On the other hand, in a second example 606 for a dark environment, a second visual indication 608 indicates a greater amount of headroom for displaying a digital image 122.

[0096] Thus, the amount of HDR headroom depends on the environment in which the display device 104 is located. The brighter the surrounding environment, the brighter the display, which means less headroom is available. Thus, when in a dark environment, the overall display brightness drops, which means there is more headroom. Thus, the visualization of HDR display capabilities in this example can be used to account for changing environmental conditions, changes in the high dynamic range 130 of different display devices 104, differences in views of target display devices, etc. For example, the visualization provides creative professionals with the ability to see these changes and react accordingly as part of editing the digital image 122, which is not possible with conventional techniques.

[0097] Figure 7 Depicted in more detail is shown by Figure 2 700 of generating a visualization of display capabilities as an overlay by the capability visualization module 216 of the example. The capability visualization module 216 in this example includes an overlay module 702 that is configured to indicate which pixels included in the digital image 122 are supported by HDR capabilities and which are not supported by HDR capabilities. As previously described, the histogram 302 includes a visualization of the range of luminance values ​​that are supported and not supported by the high dynamic range 130 by defining an input of HDR capabilities, for example, as specified by a user, as determined for a particular display device 104, etc.

[0098] The digital image 122 is then displayed with visualization characteristics that define which pixels are included in the high dynamic range 130 and are supported, and which pixels are included in the high dynamic range 130 and are not supported. Color coding is utilized in the illustrated implementation, where yellow pixels are included in the high dynamic range 130 and are supported, and red pixels are included in the high dynamic range 130 and are not supported. Pixels within the standard dynamic range are displayed in the user interface “as is.” Likewise, in this manner, the capability visualization module 216 supports insight into the composition of the digital image 122 that is not possible using conventional techniques.

[0099] Figure 8 Depicted in more detail is shown by Figure 2 800 of an example implementation of the capability visualization module 216 generating a visualization displaying the capability as a color code associated with the numerical value of the corresponding color channel of the pixel. In this example, the capability visualization module 216 receives an input selecting a particular pixel from the digital image 122. In response, the capability visualization module 216 generates a visualization 802 in conjunction with the histogram 302 that displays the brightness value of the corresponding pixel in the corresponding color channel (e.g., red, green, blue).

[0100] The brightness values ​​are also displayed as having characteristics indicating whether the corresponding pixel is supported by HDR capabilities. For example, the brightness value of the red channel of the pixel is indicated as having a value of "3.3" and is coded in red to indicate that the brightness value is not supported by the defined HDR capabilities. On the other hand, the brightness values ​​of the green channel and the blue channel of "2.4" and 1.1" are color coded in yellow to indicate that these brightness values ​​are supported by the defined HDR capabilities, i.e., within the first range displayed relative to the histogram 302. Therefore, in this example, the visualization as an overlay directly indicates HDR support for the corresponding pixel within the digital image 122. Similar techniques can also be used to indicate the relationship between the range of HDR brightness values ​​and the corresponding pixels within the digital image 122, examples of which are included in the discussion below and shown in the corresponding figures.

[0101] Fig.10 Depicted in more detail is shown by Figure 2 An example implementation 1000 of the range visualization module 218 generating a visualization. Fig.11 is a flow chart depicting a step-by-step procedure 1100 in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization indicating a range of luminance values ​​within a high dynamic range, the visualization configured to aid in editing of a digital image.

[0102] In this example, the histogram 302 includes an indication of the range (eg, color coding) of luminance values ​​within the HDR, which corresponds to Figure 3 310, second f-stop 312, third f-stop 314, and fourth f-stop 316 of the range visualization module 218. In response to selection of the "Visualize HDR" option in the user interface circled in the illustration, the correlation module 1002 of the range visualization module 218 outputs these indications. Pixels associated with those ranges are then shown within the digital image 122 with those indications (i.e., colors coded from cyan to magenta).

[0103] For example, pixels of the digital image 122 within the standard dynamic range are displayed by the range visualization module 218 “as is.” However, pixels of the digital image 122 in the high dynamic range are displayed with corresponding visualization characteristics associated with an indication of the range displayed relative to the histogram 302. As a result, the user interface provides feedback as to which range of luminance values ​​are used for corresponding pixels within the digital image 122. In the example shown, portions of the iceberg and sky are one to two stops above SDR white and are displayed in cyan and blue. Brighter areas that are three to four stops above SDR white are displayed in purple and magenta.

[0104] Thus, in this example, for a plurality of pixels 126 in the digital image 122, the brightness values ​​204 are again detected (e.g., by the brightness detection module 202) (block 1102). The brightness values ​​204 are then assigned to respective ranges of the plurality of ranges by the range visualization module 218 of the visualization generation module 140 (block 1104). Visualization characteristics are assigned to at least one range of the plurality of ranges by the range visualization module 218 (block 1106), and the digital image 122 is displayed with the assigned visualization characteristics for pixels included in the at least one range of brightness values ​​204 (block 1108). As a result, in this example, the visualization uses correlation between the visualization characteristics of the digital image 122 and the visualization characteristics of the histogram 302 to provide insight into the HDR tonality of the digital image 122.

[0105] Fig.12 Depicted in more detail is shown by Figure 2 The point curve visualization module 220 generates an example implementation 1200 of a visualization as point curves. Fig.13 is a flow chart depicting a step-by-step procedure 1300 in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization as a point curve as a mapping between luminance values ​​detected from a digital image and output luminance values ​​over a standard dynamic range and a high dynamic range.

[0106] As before, the brightness detection module 202 is used to detect brightness values ​​204 from the digital image 122 (block 1302). Based on these values, the point curve visualization module 220 generates the point curve 1202 as a map.

[0107] The point curve 1202 is user selectable, for example, to adjust the mapping between the luminance values ​​204 detected from the digital image 122 and the output luminance values ​​over the standard dynamic range and the high dynamic range (block 1304), which is displayed in a user interface to support user input to adjust the mapping (block 1306). For example, points along the point curve are user selectable to adjust the output luminance values ​​of corresponding pixels of the digital image 122.

[0108] Point curve 1202 is divided into two parts, SDR (lower left quadrant) and HDR in the other three quadrants. The HDR part provides direct and precise control over highlights. The center of the frame represents the SDR white level, with a value of five hundred, representing four f-stops above SDR white. Therefore, the scale used to depict brightness values ​​in the standard dynamic range in the example shown is different from the scale used to depict brightness values ​​in the high dynamic range, such as Figure 3 302. For example, the high dynamic range includes a larger range of brightness values ​​than the standard dynamic range. Therefore, in order to "fit these in", in this example, the standard dynamic range uses a linear scale for the point curve 1202, while the high dynamic range 306 uses a logarithmic scale to indicate the corresponding brightness values.

[0109] Fig.14 Depicted in more detail is shown by Figure 2 The preview visualization module 222 generates an example implementation 1400 of a visualization as a standard dynamic range preview of a digital image that is configured for output in a high dynamic range via a point curve. Fig.15 is a flow chart describing a step-by-step procedure 1500 in an example implementation of operations that may be performed by a processing device to achieve a result of generating a visualization as a standard dynamic range preview of a high dynamic range digital image.

[0110] The preview visualization module 222 is configured to support a preview of how the HDR-capable digital image 122 will look when displayed in a standard dynamic range. Fig.14 As shown in the user interface 1402 of FIG. 1 , the digital image 122 is displayed by the display device in the user interface 1402 using a standard dynamic range and a high dynamic range of brightness values ​​(block 1502). Input is received via the user interface 1402 to display the digital image using a standard dynamic range (block 1504), such as by selecting "SDR display preview". Sliders are also included for adjusting tone mapping of brightness, contrast, sharpness, highlights, shadows, whites, saturation, etc.

[0111] In response, the preview visualization module 222 converts the brightness values ​​of the pixels in the digital image 122 that are in the high dynamic range to the standard dynamic range (block 1506). The digital image is then displayed in the user interface as having the converted brightness values ​​in the standard dynamic range (block 1508). Thus, the representation supports the ability to switch "back and forth" between displaying the digital image 122 using SDR and using both SDR and HDR simultaneously. Various other examples are also contemplated.

[0112] Example Systems and Devices

[0113] Fig.16An example system is shown generally at 1600, including an example computing device 1602, which is representative of one or more computing systems and / or devices that implement the various techniques described herein. This is illustrated by including a visualization generation module 140. For example, computing device 1602 may be configured as a server of a service provider, a device associated with a client (e.g., a client device), a system on a chip, and / or any other suitable computing device or computing system.

[0114] The example computing device 1602 shown in the figure includes a processing device 1604, one or more computer-readable media 1606, and one or more I / O interfaces 1608 that are communicatively coupled to each other. Although not shown, the computing device 1602 further includes a system bus or other data and command transmission system that couples various components to each other. The system bus can include any one or combination of different bus structures, such as a memory bus or memory controller, a peripheral bus, a universal serial bus, and / or any processor or local bus utilizing various bus architectures. Various other examples are also contemplated, such as control lines and data lines.

[0115] Processing device 1604 represents the functionality of performing one or more operations using hardware. Thus, processing device 1604 is shown as including hardware elements 1610 that may be configured as processors, functional blocks, etc. This includes being implemented in hardware as a dedicated integrated circuit or other logic device formed using one or more semiconductors. Hardware elements 1610 are not limited by the materials from which they are formed or the processing mechanisms employed therein. For example, a processor may be configured as a semiconductor and / or a transistor (e.g., an electronic integrated circuit (IC)). In such a context, processor executable instructions are electronic executable instructions.

[0116] Computer-readable storage media 1606 is shown to include memory / storage 1612 that stores instructions executable to cause processing device 1604 to perform operations. Memory / storage 1612 represents memory / storage capacity associated with one or more computer-readable media. Memory / storage 1612 includes volatile media (such as random access memory (RAM)) and / or non-volatile media (such as read-only memory (ROM), flash memory, optical disks, magnetic disks, etc.). Memory / storage 1612 includes fixed media (e.g., RAM, ROM, fixed hard drives, etc.) and removable media (e.g., flash memory, removable hard drives, optical disks, etc.). Computer-readable media 1606 can be configured in various other ways as further described below.

[0117] Input / output interface(s) 1608 represent functionality that allows a user to input commands and information to computing device 1602, and also allows information to be presented to the user and / or other components or devices using various input / output devices. Examples of input devices include a keyboard, a cursor control device (e.g., a mouse), a microphone, a scanner, touch functionality (e.g., a capacitive sensor or other sensor configured to detect physical touch), a camera (e.g., employing visible or invisible wavelengths such as infrared frequencies to recognize movement as gestures that do not involve touch), etc. Examples of output devices include a display device (e.g., a monitor or projector), speakers, a printer, a network card, a tactile response device, etc. Thus, computing device 1602 may be configured in various ways as further described below to support user interaction.

[0118] Various techniques are described herein in the general context of software, hardware elements, or program modules. Typically, such modules include routines, programs, objects, elements, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The terms "module," "function," and "component" as used herein typically represent software, firmware, hardware, or a combination thereof. The features of the techniques described herein are platform-independent, which means that these techniques can be configured on various commercial computing platforms with various processors.

[0119] An implementation of the described modules and techniques is stored on or transmitted via some form of computer-readable media. Computer-readable media includes various media accessed by computing device 1602. By way of example and not limitation, computer-readable media include "computer-readable storage media" and "computer-readable signal media."

[0120] "Computer-readable storage media" refers to media and / or devices that are capable of persistent and / or non-transient storage of information (e.g., instructions stored thereon that can be executed by a processing device) as compared to simple signal transmission, carrier waves, or the signal itself. Therefore, computer-readable storage media refers to non-signal bearing media. Computer-readable storage media include hardware, such as volatile and non-volatile, removable and non-removable media and / or storage devices implemented in a method or technology suitable for storing information, such as computer-readable instructions, data structures, program modules, logic elements / circuits, or other data. Examples of computer-readable storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical storage device, hard disk, cassette, magnetic tape, magnetic disk storage device or other magnetic storage device, or other storage device, tangible media, or an article suitable for storing the desired information and accessible by a computer.

[0121] "Computer-readable signal media" refers to signal-bearing media that is configured to transmit instructions to the hardware of the computing device 1602, such as via a network. Signal media typically embody computer-readable instructions, data structures, program modules, or other data in a modulated data signal, such as a carrier wave, a data signal, or other transport mechanism. Signal media also include any information delivery media. The term "modulated data signal" means a signal that has one or more of its characteristics set or changed in a manner that encodes information in the signal. By way of example and not limitation, communication media include wired media such as a wired network or direct wired connection, and wireless media such as acoustic, RF, infrared, and other wireless media.

[0122] As previously described, hardware elements 1610 and computer-readable media 1606 represent modules, programmable device logic, and / or fixed device logic implemented in hardware, which in some embodiments are used to implement at least some aspects of the techniques described herein, such as executing one or more instructions. Hardware includes components of integrated circuits or systems on a chip, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), complex programmable logic devices (CPLDs), and other implementations in silicon or other hardware. In this case, the hardware operates as a processing device that performs program tasks defined by instructions and / or logic embodied by the hardware, as well as hardware (e.g., the computer-readable storage medium described previously) for storing instructions for execution.

[0123] The combination of the foregoing is also used to implement the various technologies described herein. Therefore, software, hardware, or executable modules are implemented as one or more instructions and / or logic embodied on some form of computer-readable storage medium and / or by one or more hardware elements 1610. Computing device 1602 is configured to implement specific instructions and / or functions corresponding to software and / or hardware modules. Therefore, for example, by using computer-readable storage media and / or hardware elements 1610 of processing device 1604, the implementation of a module that can be executed as software by computing device 1602 is at least partially implemented in hardware. Instructions and / or functions can be performed / operated by one or more manufactured products (e.g., one or more computing devices 1602 and / or processing devices 1604) to implement the technology, modules, and examples described herein.

[0124] The technology described herein is supported by various configurations of computing device 1602 and is not limited to the specific examples of the technology described herein. The functionality may also be implemented in whole or in part using a distributed system, such as on a "cloud" 1614 via a platform 1616 as described below.

[0125] The cloud 1614 includes and / or represents a platform 1616 for resources 1618. The platform 1616 abstracts the underlying functionality of the hardware (e.g., servers) and software resources of the cloud 1614. The resources 1618 include applications and / or data that can be used when performing computer processing on a server remote from the computing device 1602. The resources 1618 can also include services provided over the Internet and / or over a subscriber network such as a cellular or Wi-Fi network.

[0126] The platform 1616 abstracts resources and functionality to connect the computing device 1602 with other computing devices. The platform 1616 is also used to abstract scaling of resources to provide a corresponding level of scaling to the demand for resources 1618 encountered that is implemented via the platform 1616. Thus, in an interconnected device embodiment, the implementation of the functionality described herein may be distributed throughout the system 1600. For example, the functionality may be implemented in part on the computing device 1602 and via the platform 1616 that abstracts the functionality of the cloud 1614.

[0127] In implementations, platform 1616 employs a "machine learning model" configured to implement the techniques described herein. A machine learning model refers to a computer representation that can be fine-tuned (e.g., trained and retrained) based on inputs to approximate unknown functions. In particular, the term machine learning model can include a model that learns from and makes predictions about known data using an algorithm to learn and relearn by analyzing training data to generate outputs that reflect the patterns and properties of the training data. Examples of machine learning models include neural networks, convolutional neural networks (CNNs), long short-term memory (LSTM) neural networks, decision trees, and the like.

[0128] Although the invention has been described in language specific to structural features and / or methodological acts, it should be understood that the invention defined in the appended claims is not necessarily limited to the specific features or acts described. Instead, the specific features and acts are disclosed as example forms of implementing the claimed invention.

Claims

1. A method implemented by a processing device, the method comprising: detecting, by a processing device, brightness values ​​in a standard dynamic range and a high dynamic range from a digital image; generating, by the processing device, a histogram indicating a brightness distribution of the brightness values ​​for at least one color channel, the brightness distribution indicating a relative number of pixels from the digital image having corresponding brightness values ​​in the standard dynamic range and the high dynamic range; as well as The histogram is displayed in a user interface by the processing device. 2 . The method of claim 1 , wherein the histogram indicates relative numbers of pixels from the digital image that correspond to respective luminance values ​​in the standard dynamic range and the high dynamic range. 3 . The method of claim 1 , wherein the histogram comprises a first portion and a second portion, the first portion comprising luminance values ​​in the standard dynamic range, the second portion comprising luminance values ​​in the high dynamic range. 4 . The method of claim 3 , wherein a scaling for the luma values ​​in the first portion in the standard dynamic range is different than a scaling for the luma values ​​in the second portion in the high dynamic range. The method of claim 3 , wherein the second portion comprises a representation of a plurality of intervals of the luminance values ​​in the high dynamic range. The method according to claim 5 , wherein the plurality of intervals respectively correspond to relative light amounts that are doubled in successive intervals. The method of claim 1 , wherein the histogram is generated for a plurality of the color channels.

8. The method of claim 7, wherein the plurality of the color channels comprises a red channel, a green channel, and a blue channel.

9. The method of claim 1, wherein the histogram is displayed in the user interface along with the digital image and a representation of at least one operation that a user can select to edit the digital image and display corresponding changes to the histogram in real time.

10. A computing device comprising: Processing equipment; as well as A computer-readable storage medium storing instructions, wherein the instructions, in response to being executed by the processing device, cause the processing device to perform operations, the operations comprising: Receiving an input defining a high dynamic range (HDR) capability; detecting brightness values ​​in a standard dynamic range and a high dynamic range from a digital image; and A visualization is generated that indicates which of the luminance values ​​of the digital image are supported by the HDR capability and which of the luminance values ​​are not supported by the HDR capability. 11 . The computing device of claim 10 , wherein the high dynamic range (HDR) capability is based on a hardware device capability of a display device or an environmental capability of an environment in which the display device is located.

12. The computing device of claim 10, wherein the input defining the high dynamic range (HDR) capability is received via a user interface.

13. The computing device of claim 10, wherein the visualization comprises a representation indicating a range of the brightness values ​​in the histogram that are supported by the high dynamic range (HDR) capability, and a representation indicating a range of the brightness values ​​in the histogram that are not supported by the high dynamic range (HDR) capability.

14. The computing device of claim 10, the generating of the visualization comprising: assigning the brightness value to a corresponding range in a plurality of ranges; assigning a first visualization characteristic for a first said range within said high dynamic range to said luminance value supported by said high dynamic range (HDR) capability; assigning a second visualization characteristic for a second said range within said high dynamic range to said luminance value not supported by said high dynamic range (HDR) capability; as well as The digital image is displayed having the first specified visual properties for pixels included in the first said range and the second specified visual properties for pixels included in the second said range.

15. The computing device of claim 14, wherein the generating of the visualization further comprises pixels acquired from the digital image having brightness values ​​within the standard dynamic range.

16. A system comprising: A high dynamic range (HDR) input module implemented by the processing device and configured to receive an input defining high dynamic range (HDR) capabilities available at the display device; as well as A visualization generation module is implemented by the processing device and is configured to: Receiving user input selecting pixels of a digital image detecting brightness values ​​of a plurality of color channels associated with the pixel; as well as A visualization is generated that indicates whether the luminance value is supported by the HDR capabilities available at the display device.

17. The system of claim 16, wherein the high dynamic range (HDR) capability is based on hardware device capabilities of the display device.

18. The system of claim 16, wherein the high dynamic range (HDR) capability is based on an environmental capability of an environment in which the display device is located.

19. The system of claim 16, wherein the visualization comprises color coding.

20. The system of claim 16, wherein the visualizations respectively include numerical values ​​for the luma values, the numerical values ​​including associated visualization characteristics indicating whether the luma values ​​are supported by the HDR capability or not supported by the HDR capability.

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