Apparatus and method for improving image data exchange based on perceptual luminance non-linearity between different display functions

Abstract

To provide a device and method for improving perceptual nonlinearity-based image data exchange across different display capabilities.SOLUTION: A handheld image processor has a data receiver that is configured to receive reference encoded image data. The data includes reference code values, which are encoded by an external coding system. The reference code values represent reference gray levels, which are selected using a reference grayscale display function based on perceptual non-linearity of human vision adapted at different light levels to spatial frequencies. The image processor also has a data converter that is configured to access a code mapping between the reference code values and device-specific code values of the image processor. The device-specific code values are configured to produce gray levels that are specific to the image processor. Based on the code mapping, the data converter is configured to transcode the reference encoded image data into device-specific image data, which is encoded with the device-specific code values.SELECTED DRAWING: Figure 5

Description

Technical Field

[0001] Cross - Reference to Related Applications This application claims the benefit of U.S. Provisional Patent Application No. 61 / 567,579, filed on Dec. 6, 2011; U.S. Provisional Patent Application No. 61 / 674,503, filed on Jul. 23, 2012; and U.S. Provisional Patent Application No. 61 / 703,449, filed on Sep. 12, 2012. The contents of these applications are hereby incorporated by reference in their entirety for all purposes.

[0002] The Technology of the Invention The present invention generally relates to image data. More particularly, certain embodiments of the present invention relate to image data exchange based on perceptual non - linearities between different display functions.

Background Art

[0003] Advances in technology have enabled modern display designs to render image and video content with significant improvements in various quality characteristics for the same content that was rendered on displays just a short time ago. For example, some newer displays can render content with a higher dynamic range (DR) than the standard dynamic range (SDR) of normal or standard displays.

[0004] For example, some modern liquid crystal displays (LCDs) have an illumination unit (such as a backlight unit, a side - light unit, etc.) that provides a field of light whose individual portions can be modulated separately from the modulation of the liquid crystal alignment state of the active LCD elements. This dual - modulation technique can be extended (e.g., to N modulation layers where N is an integer greater than 2) by a controllable intervening layer (such as multiple layers of individually controllable LCD layers) in the electro - optical configuration of the display.

[0005] In contrast, some existing displays have a dynamic range (DR) that is significantly narrower than high dynamic range (HDR). Typical cathode ray tubes (CRTs), liquid crystal displays (LCDs) with a constant fluorescent white backlight, or mobile devices, computer pads, gaming consoles, televisions (TVs), and computer monitor devices using plasma screen technology may be restricted to approximately three digits in their DR rendering capabilities. Thus, such existing displays are typical of the standard dynamic range (SDR), sometimes also referred to as "low dynamic range (LDR)" in relation to HDR.

Prior Art Documents

Non-Patent Documents

[0006]

Non-Patent Document 1

Non-Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0007] Images captured by an HDR camera may have a scene-referred HDR that is significantly larger than the dynamic range of most display devices, if not all. Scene-referred HDR images contain a large amount of data and may be converted to post-production formats (e.g., 8-bit RGB, YCbCr, or HDMI (registered trademark) video signals with deep color options; 1.5 Gbps SDI video signals with a 10-bit 4:2:2 sampling rate; 3 Gbps SDI with a 12-bit 4:4:4 or 10-bit 4:2:2 sampling rate; and other video or image formats) to facilitate transmission and storage. Post-production images have a much smaller dynamic range than scene-referred HDR images. Further, when the image is delivered to the end-user's display device for rendering, device-specific and / or manufacturer-specific image conversions occur along the way, causing a visually perceptible amount of error in the rendered image compared to the original scene-referred HDR image. **Means for Solving the Problem**

[0008] The approaches described in the above section could have been pursued but are not necessarily approaches that were previously conceived or pursued. Thus, unless otherwise stated, none of the approaches described in that section should be assumed to be eligible for prior art merely by virtue of being included in that section. Similarly, unless otherwise stated, the problems identified with respect to one or more of the approaches should not be assumed to have been recognized in any prior art based on that section. **Brief Description of the Drawings**

[0009] The present invention, by way of example and not limitation, is illustrated in the figures of the accompanying drawings. In the drawings, like reference numerals refer to like elements.

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[0010] Exemplary embodiments related to image data exchange based on perceptual luminance non - linearity between displays of different functions are described in this document. In the following description, for the sake of explanation, numerous individual details are described to provide a complete understanding of the present invention. However, it will be apparent that the present invention can be practiced without such individual details. On the other hand, well - known structures and devices are not described in exhaustive detail to avoid obscuring, burying, or obfuscating the present invention.

[0011] The exemplary embodiments are described in this document according to the following outline.

[0012] 1. Overview 2. Contrast Sensitivity Function (CSF) Model 3. Perceptual Non - linearity 4. Digital Code Values and Gray Levels 5. Model Parameters 6. Variable Spatial Frequency 7. Function Model 8. Exchange of Image Data Based on the Reference GSDF 9. Conversion of the Reference Encoded Image Data 10. Exemplary Process Flow 11. Implementation Mechanism - Overview of Hardware 12. Numbered Embodiments, Equivalents, Extensions, Alternatives, and Others 〈1. Overview〉 This overview presents a basic description of some aspects of an embodiment of the present invention. It should be noted that this overview is not an exhaustive or comprehensive summary of all aspects of its exemplary embodiments. Furthermore, this overview is not intended to identify any particularly significant aspects or elements of its exemplary embodiments, nor is it generally intended to define any scope of the present invention, particularly of its exemplary embodiments. This overview simply presents some concepts related to its exemplary embodiments in a condensed and simplified form and should be understood merely as a conceptual introduction to the more detailed description of the subsequent exemplary embodiments.

[0013] Human vision may not perceive the difference between two luminance values if they are not sufficiently different from each other. Human vision only perceives a difference when the luminance values differ by at least the just noticeable difference (JND). Due to the non-linearity of human vision perception, the magnitude of an individual JND is not of uniform magnitude over a range of light levels, nor is it uniformly scaled, but rather varies with different individual light levels. Furthermore, due to the non-linearity of perception, the magnitude of an individual JND is not of uniform magnitude over a range of spatial frequencies at a particular light level, nor is it uniformly scaled, but rather varies with different spatial frequencies below a certain cutoff spatial frequency.

[0014] Encoded image data with equal-sized or linearly scaled luminance quantization bins does not match the perceptual non-uniformity of human vision. Encoded image data with fixed spatial frequency luminance quantization bins does not match the perceptual non-uniformity of human vision. Under these techniques, when codewords are assigned to represent the quantized luminance values, too many codewords may be distributed in a particular region (e.g., a bright region) within the above light level range, while too few codewords may be distributed in a different region (e.g., a dark region) of the above light level range.

[0015] In the over-distribution region, many of the codewords may not produce a perceptual difference and thus are effectively wasted. In the under-distribution region, two adjacent codewords produce a perceptual difference much larger than the JND, potentially resulting in contour distortion (also known as banding) visual artifacts.

[0016] Under the techniques described in this document, for a wide range of light levels (e.g., 0 to 12,000 cd / m 2)To determine the JND over a range, a contrast sensitivity function (CSF) model may be used. In one exemplary embodiment, the peak JND as a function of spatial frequency at a particular light level is selected to represent the quantum of human perception at that particular light level. The selection of the peak JND conforms to the behavior of human vision that adapts to an enhanced level of visual perceptibility when viewing backgrounds of nearby but different luminance values. This is sometimes referred to in the fields of video and image display as the crispening effect and / or Whittle's Crispening effect, and is described as such herein. In the usage herein, the term "light adaptation level" may be used to refer to the light level at which the (e.g., peak) JND is selected / determined, assuming that human vision is adapted to that light level. The peak JND described herein varies across spatial frequencies at various light adaptation levels.

[0017] In the usage herein, the term "spatial frequency" may refer to the rate of spatial modulation / variation in an image (where the rate is calculated in relation to or with respect to spatial distance rather than with respect to time). In contrast to the usual approach of fixing the spatial frequency to a particular value, the spatial frequency described herein may vary, for example, within or over a range. In some embodiments, the peak JND may be limited within a particular spatial frequency range (e.g., 0.1 to 5.0, 0.01 to 8.0 cycles / degree or a smaller or larger range).

[0018] Based on the CSF model, a reference gray scale display function (GSDF) can be generated. In some embodiments, a very wide field of view is assumed for the CSF model in order to generate a reference GSDF that better supports the entertainment display field. The GSDF refers to a set of reference digital code values (or reference code words), a set of reference gray levels (or reference luminance values), and the mapping between the two sets. In an exemplary embodiment, each reference digital code value corresponds to a quantum of human perception represented by a JND (e.g., the peak JND at the light adaptation level). In an exemplary embodiment, an equal number of reference digital code values can correspond to the quanta of human perception.

[0019] The GSDF is obtained by cumulatively adding JNDs from an initial value. In an exemplary embodiment, a central code word value (e.g., 2048 for a 12-bit code space) is given as the initial value to the reference digital code. The initial value of the reference digital code can correspond to an initial reference gray level (e.g., 100 cd / m 2 )). Other reference gray levels for other values of the reference digital code are obtained by positively cumulatively adding (adding) the JND when the reference digital code is incremented one by one, and negatively cumulatively adding (subtracting) the JND when the reference digital code is decremented one by one. In an exemplary embodiment, a quantity such as a contrast threshold may be used in the calculation of the reference values in the GSDF instead of the JND. These quantities actually used in the calculation of the GSDF may be defined as unitless ratios and may differ from the corresponding JNDs only by known or determinable multipliers, divisors, and / or offsets.

[0020] The symbol space may be selected to include all reference digital code values in the GSDF. In some embodiments, the symbol space in which all reference digital code values exist may be one of a 10-bit symbol space, an 11-bit symbol space, a 12-bit symbol space, a 13-bit symbol space, a 14-bit symbol space, a 15-bit symbol space, or a larger or smaller symbol space.

[0021] A large symbol space (>15 bits) may be used to accommodate all reference digital code values, but in certain embodiments, the most efficient symbol space (e.g., 10 bits, 12 bits, etc.) is used to accommodate all reference digital code values generated in the reference GSDF.

[0022] The reference GSDF may be used to encode image data captured or generated by, for example, an HDR camera, a studio / system, or other systems with a scene-reference HDR that is significantly larger than the dynamic range of most, if not all, display devices. The encoded image data may be provided to downstream devices in a wide variety of delivery or transmission methods (e.g., 8-bit RGB, YCbCr, or HDMI® video signal with deep color options; 1.5 Gbps SDI video signal with 10-bit 4:2:2 sampling rate; 3 Gbps SDI with 12-bit 4:4:4 or 10-bit 4:2:2 sampling rate; and other video or image formats).

[0023] In some embodiments, since adjacent reference digital code values in the reference GSDF correspond to gray levels within the JND, in the image data encoded based on the reference GSDF, the details distinguishable by human vision can be fully or substantially preserved. A display that fully supports the reference GSDF may potentially render images without banding or contour distortion artifacts.

[0024] Image data encoded based on a reference GSDF (or reference encoded image data [reference encoded image data]) may be used to support a wide variety of less capable displays that do not fully support all reference luminance values in the reference GSDF. Since the reference encoded image data has all perceptual details within the supported luminance range (which may be designed to be a superset of what the display supports), the reference digital code values may be optimally and efficiently transcoded to display-specific digital code values in a way that preserves as much detail as possible that a particular display can support and causes as few visually perceptible errors as possible. Additionally and / or optionally, decontouring and dithering may be performed in connection with or as part of the transcoding from reference digital code values to display-specific digital code values to further improve image or video quality.

[0025] The techniques described herein are not color space dependent. They may be used in the RGB color space, the YCbCr color space or different color spaces. Further, techniques for deriving reference values (e.g., reference digital code values and reference gray levels) using JND that varies with spatial frequency may be applied to different channels other than the luminance channel (e.g., one of the red, green and blue channels) in different color spaces (e.g., RGB) that may or may not include a luminance channel. For example, a reference blue value may be derived using JND applicable to the blue color channel instead of a reference gray level. Thus, in some embodiments, grayscale may be used instead of color. Additionally and / or optionally, different CSF models may be used instead of Barten's model, and different model parameters may be used for the same CSF model.

[0026] In some embodiments, the mechanisms described herein form part of a media processing system including, but not limited to, a handheld device, a gaming console, a television, a laptop computer, a netbook computer, a cellular radiotelephone, an electronic book reader, a point-of-sale terminal, a desktop computer, a computer workstation, a computer kiosk, or various other types of terminals and media processing units.

[0027] Various modifications to the preferred embodiments and general principles and features described herein will be apparent to those skilled in the art. Accordingly, the disclosure is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features described herein.

[0028] 〈2. Contrast Sensitivity Function (CSF) Model〉 The sensitivity of human vision to spatial structures in a rendered image can be best described by the contrast sensitivity function (CSF). This describes contrast sensitivity as a function of spatial frequency (or the rate of spatial modulation / variation in an image perceived by a human observer). In the usage herein, contrast sensitivity S may be considered as the gain in the neural signal processing of human vision, while contrast threshold C T may be determined from the reciprocal of the contrast sensitivity. For example: Contrast sensitivity = S = 1 / C T (1) In the usage herein, "contrast threshold" refers to or may relate to the lowest value of (relative) contrast (e.g., the minimum perceptible difference) necessary for the human eye to perceive a contrast difference. In some embodiments, the contrast threshold may be depicted as a function of the minimum perceptible difference divided by the light adaptation level over a range of luminance values.

[0029] In some embodiments, the contrast threshold may be directly measured in experiments without using any CSF model. However, in some other embodiments, the contrast threshold may be determined based on a CSF model. The CSF model may be constructed using several model parameters and may be used to derive the GSDF. The quantization step of the GSDF in terms of gray level depends on and varies with the light level and spatial frequency characterized by the luminance value. An exemplary embodiment may be implemented based on one or more of various CSF models such as those described in Non-Patent Document 1 (hereinafter, Barten's model or Barten's CSF model) or those described in Non-Patent Document 2 (hereinafter, Daily's model). In the context of exemplary embodiments of the present invention, the contrast threshold used to generate the reference gray scale display function (GSDF) may be derived experimentally, theoretically, using a CSF model, or a combination thereof.

[0030] In the usage in this paper, the GSDF may refer to the mapping of a plurality of digital code values (e.g., 1, 2, 3, …, N) to a plurality of gray levels (L1, L2, L3, …, L N ). Here, as shown in Table 1, the digital code value represents the index value of the contrast threshold, and the gray level corresponds to the contrast threshold.

[0031]

Table 1

[0032] C(i)=(L i+1 -L i ) / (L i+1 +L i ) =(L i+1 -Lmean (i,i + 1)) / L mean (i,i + 1) = ~(1 / 2)ΔL / L (2) Here, C(i) represents the contrast for the luminance range with L i and L i+1 as the two ends. L mean (i,i + 1) is the arithmetic mean of two adjacent gray levels L i and L i+1 . The contrast C(i) is arithmetically related to the Weber fraction by a factor of 2. Here, ΔL represents (L i+1 - L i ), and L represents one of L i , L i+1 or an intermediate value between L i and L i+1 .

[0033] In some embodiments, the GSDF generator may set the contrast C(i) to be equal to or proportional to a contrast threshold (e.g., C i (i)) at a certain luminance level L between L i+1 including both ends. T (i)) at a certain luminance level L between L

[0034] C(i)=kC T (i) (3) Here, k represents a multiplication constant. In the context of embodiments of the present invention, other descriptive statistics / definitions (e.g., geometric mean, median, mode, variance, or standard deviation) and / or scaling (×2, ×3, divide by a scaling factor, or multiply by a scaling factor, etc.) and / or offset (+1, +2, -1, -2, subtract an offset or add an offset, etc.) and / or weighting (e.g., assign the same or different weighting factors to two adjacent gray levels) may be used to relate the contrast threshold to the contrast for the purpose of calculating the gray levels in the GSDF.

[0035] As calculated by equations (1), (2), and (3), the contrast or contrast threshold is a relative value and can thus be a dimensionless quantity. (Thus, for example, S can also be a dimensionless quantity.) The CSF model can be constructed from basic contrast threshold measurements or calculations based on the CSF that depicts the CSF model. Unfortunately, human vision is complex, adaptive, and non-linear, and thus there is no single CSF curve that describes human vision. Instead, a family of CSF curves can be generated based on the CSF model. Even with the same CSF model, different values of the model parameters will result in different plots for the family of CSF curves.

[0036] 〈3. Nonlinearity of Perception〉 Figure 1 shows an exemplary family of CSF curves spanning multiple light adaptation levels. For illustrative purposes only, the topmost CSF curve depicted in Figure 1 is for a light adaptation level at a luminance value of 1000 candela per square meter (cd / m 2 or "nits"), and the other lower curves are for light adaptation levels at luminance values that decrease by a factor of 10 each. A notable feature that can be read from these CSF curves is that as the luminance increases (as the light adaptation level increases), the overall contrast sensitivity, including the maximum (or peak) contrast sensitivity, increases. The peak spatial frequency at which the contrast sensitivity peaks on the CSF curve in Figure 1 shifts to higher spatial frequencies. Similarly, the maximum perceivable spatial frequency (cutoff frequency) on the CSF curve, which is the intercept with the horizontal axis (spatial frequency axis) of the CSF curve, also increases.

[0037] In one exemplary embodiment, the CSF function that gives the family of CSF curves shown in Figure 1 may be derived using Barten's CSF model that takes into account several key effects related to human perception. An exemplary CSF S(u) (or the reciprocal of the corresponding contrast threshold m t ) under Barten's CSF model may be calculated as shown in equation (4) below.

[0038]

Number

[0039] The optical modulation transfer function M opt may be given as follows.

[0040]

Number

[0041] The CSF model of Barton discussed above can be used to describe the non-linearity of perception with respect to luminance. Other CSF models may be used to describe the non-linearity of perception. For example, Barton's CSF model does not take into account the effect of accommodation, which causes a decrease in the cut-off spatial frequency in the high spatial frequency region of the CSF. This decrease effect due to accommodation may be expressed as a function of the decreasing viewing distance.

[0042] For example, for viewing distances exceeding 1.5 meters, the maximum cut-off spatial frequency depicted by Barton's CSF model can be reached, but it does not affect the effectiveness of Barton's model as an appropriate model for describing the non-linearity of perception. However, for distances shorter than 1.5 meters, the effect of accommodation begins to become significant and reduces the accuracy of Barton's model.

[0043] Thus, for tablet displays with closer viewing distances such as 0.5 meters or smartphones that can have viewing distances as close as about 0.125 meters, Barton's CSF model may not be optimally adjusted.

[0044] In some embodiments, the daily CSF model that takes into account the accommodation effect may be used. In a particular embodiment, the daily CSF model may be constructed by modifying, for example, the optical modulation transfer function M of Equation (5) based in part on Barton's CSF S(u) of Equation (4) above. opt to be modified.

[0045] 〈4. Digital Code Values and Gray Levels〉 The GSDF as shown in Table 1 uses digital code values to map the non-linearity of perception to represent gray levels associated with contrast thresholds in human vision. The gray levels including all the mapped luminance values may be distributed in a way that they are optimally spaced to match the perceptual non-linearity of human vision.

[0046] In some embodiments, when the maximum number of gray levels in the GSDF is large enough for the maximum range of luminance values, the digital code values in the GSDF may be used in such a way as to achieve the minimum number of gray levels (e.g., less than a total of 4096 digital code values) without causing the visibility of gray-level step transitions (e.g., appearing as false contours or bands in an image; or color shifts in dark regions of the image).

[0047] In some other embodiments, a limited number of digital code values may be used to represent a wide dynamic range of gray levels. For example, when the maximum number of gray-scale levels in the GSDF is not large enough for the maximum range of gray-scale levels (e.g., digital code values of an 8-bit representation for a range of gray-scale levels from 0 to 12,000 nits), the GSDF may still be used in such a way as to achieve the minimum number of gray levels (e.g., less than a total of 256 digital code values) to reduce or minimize the visibility of gray-level step transitions. In such a GSDF, the amount / degree of perceptible errors / artifacts of the step transitions may be evenly distributed through a relatively small number of gray-level hierarchies in the GSDF. In the usage in this document, the terms "gray-scale level" or "gray level" may be used interchangeably and may refer to the expressed luminance value (the quantized luminance value expressed in the GSDF).

[0048] The gray levels in the GSDF can be derived by integrating or accumulating the contrast thresholds through various light adaptation levels (at different luminance values). In some embodiments, the quantization step between gray levels may be chosen such that the quantization step between any two adjacent gray levels falls within the JND. The contrast threshold at a particular light adaptation level (or luminance value) may not be greater than the just noticeable difference (JND) at that particular adaptation level. The gray levels may be derived by integrating or accumulating the fraction of the contrast threshold (or JND). In some embodiments, the number of digital code values is more than sufficient to represent all JNDs in the dynamic range in which luminance is represented.

[0049] The contrast threshold or, conversely, the contrast sensitivity used to calculate the gray scale levels may be selected from the CSF curve at different spatial frequencies other than a fixed spatial frequency for a particular light adaptation level (or luminance value). In some embodiments, each of the contrast thresholds is selected from the CSF curve at the spatial frequency corresponding to the peak contrast sensitivity for the light adaptation level (e.g., due to the Whitlatch sharpening effect). Further, the contrast threshold may be selected from the CSF curve at various spatial frequencies for various light adaptation levels.

[0050] An exemplary expression for calculating / accumulating the gray levels in the GSDF is as follows.

[0051]

Equation

[0052] In some embodiments, the integration of JND for deriving gray levels in the GSDF is performed by summation as shown, for example, in Equation (6). In some other embodiments, integration may be used instead of a discrete sum. The integration may be performed along an integration path determined from the CSF (for example, Equation (4)). For example, the integration path may include peak contrast sensitivities (for example, different peak sensitivities corresponding to different spatial frequencies) for all light adaptation levels in the (reference) dynamic range for the CSF.

[0053] In the usage in this document, the integration path may refer to a Visible Dynamic Range (VDR) curve that represents the non-linearity of human perception and is used to establish a mapping between a set of digital code values and a set of reference gray levels (quantized luminance values). The mapping may be required to satisfy the criterion that each quantization step (e.g., the luminance difference between two adjacent gray levels in Table 1) is smaller than the JND above or below the corresponding light adaptation level (luminance value). The instantaneous derivative of the integration path at a particular light adaptation level (luminance value) (in units of nit / space cycle) is proportional to the JND at that particular adaptation level. In the usage in this document, "VDR" or "Visual Dynamic Range" may refer to a dynamic range wider than the standard dynamic range, and may include, but is not limited to, a wide dynamic range up to the instantaneous perceptible dynamic range and color range that human vision can perceive at a moment.

[0054] Based on the techniques described in this document, an independent reference GSDF may be developed that is independent of any particular display or image processing device. In some embodiments, one or more model parameters other than the light adaptation level (luminance), spatial frequency, and angular size may be set to constant (or fixed) values.

[0055] 〈5. Model Parameters〉 In some embodiments, the CSF model is constructed with conservative model parameter values that cover a wide range of display devices. The use of conservative model parameter values provides a JND smaller than that of existing standard GSDFs. Thus, in some embodiments, the reference GSDF under the techniques described in this document can support luminance values with high accuracy that exceed the requirements of these display devices.

[0056] In some embodiments, the model parameters described herein include field-of-vision (FOV) parameters. The FOV parameters may be set to values of 45 degrees, 40 degrees, 35 degrees, 30 degrees, 25 degrees or other larger or smaller values, including those used in studio, theater or high-end entertainment systems, to support a wide range of display devices and viewing scenarios.

[0057] The model parameters described herein may include angular size parameters. This may be related to the field of vision, for example. The angular size parameters may be set to values of 45 degrees × 45 degrees, 40 degrees × 40 degrees, 35 degrees × 35 degrees, 30 degrees × 30 degrees, 25 degrees × 25 degrees or other larger or smaller values, including those used in studio, theater or high-end entertainment systems, to support a wide range of display devices and viewing scenarios. In some embodiments, the angular size parameters that are used in part to derive the reference GSDF are set to n degrees × m degrees, where both n and m may be numerical values between 30 and 40, and n and m may or may not be equal.

[0058] In some embodiments, a larger angular size (e.g., 40 degrees × 40 degrees) is used to produce a reference GSDF with a greater number of gray scale levels and thus a greater contrast sensitivity. The GSDF may be used to support a wide range of viewing and / or display scenarios (e.g., large screen video display) that may require a wide viewing angle of ~30 to 40 degrees. The GSDF with increased sensitivity due to the large angular size may be used to support widely varying viewing and display scenarios (e.g., movie theater). It is possible to select an even larger angular size, but the benefits resulting from raising the angular size significantly above a certain angular size (e.g., 40 degrees) may sometimes be relatively limited.

[0059] In some embodiments, the reference GSDF model covers a large luminance range. For example, the gray levels or quantized luminance values represented by the reference GSDF model are from 0 or approximately 0 (e.g., 10 -7 cd / m 2 ) to 12,000 cd / m 2 . The lower limit of the luminance value represented in the reference GSDF model can be 10 -7 cd / m 2 or lower or higher values (e.g., 0, 10 -5 , 10 -8 , 10 -9 cd / m 2 etc.). The GSDF can be used to support a wide range of viewing and / or display scenarios with various ambient light levels. The GSDF can be used to support a wide range of display devices with various dark black levels (in theaters, indoors or outdoors).

[0060] The upper limit of the luminance value represented in the reference GSDF model is 12,000 cd / m 2 or lower or higher values (e.g., 6000 - 8000, 8000 - 10000, 10000 - 12000, 12000 - 15000 cd / m 2 etc.). The GSDF may be used to support a wide range of viewing and / or display scenarios with a high dynamic range. The GSDF may be used to support a wide range of display devices with various maximum luminance levels (HDR TV, SDR display, laptop, tablet, handheld device, etc.).

[0061] 〈6. Variable Spatial Frequency〉 FIG. 2 shows an exemplary integration path (denoted as VDR) that may be used as an integration path for obtaining gray levels in the reference GSDF described in this document, based on an exemplary embodiment of the present invention. In embodiments, the VDR curve is used to accurately capture the peak contrast sensitivity of human vision over a high dynamic range of luminance values.

[0062] As shown in FIG. 2, the peak contrast sensitivity does not appear at a fixed spatial frequency value. Rather, it appears at a smaller spatial frequency as the light adaptation level (luminance value) decreases. This means that techniques with a fixed spatial frequency (e.g., DICOM) may significantly underestimate the contrast sensitivity of human vision for dark light adaptation levels (low luminance values). Lower contrast sensitivity leads to a higher contrast threshold, resulting in a larger quantization step in the quantized luminance value.

[0063] Unlike the Medical Digital Imaging and Communications in Medicine (DICOM) standard, the VDR curve under the techniques described in this paper does not fix the spatial frequency model parameters to fixed values such as every 4 cycles. Rather, the VDR curve changes with the spatial frequency and accurately captures the peak contrast sensitivity of human vision at multiple light adaptation levels. The VDR curve helps generate a high-precision reference GSDF by properly considering the sharpening effect due to the adaptability of human vision to a wide range of light adaptation levels. Here, the term "high-precision" means that the perceptual errors caused by the quantization of luminance values are removed or substantially reduced based on a reference GSDF that best and most efficiently captures the non-linearity of human vision within the constraints of a fixed-size code space (e.g., one of 10 bits, 12 bits, etc.).

[0064] A calculation process can be used to calculate the gray levels in the reference GSDF (e.g., Table 1). In one exemplary embodiment, the calculation process is sequential, iterative, or recursive, and iteratively determines the contrast threshold (or modulation threshold, e.g., m in Equation (4)) from the VDR curve and applies the contrast threshold to obtain a series of gray levels in the reference GSDF. This calculation process may be implemented using the following Equation (7). t ) and applies the contrast threshold to obtain a series of gray levels in the reference GSDF. This calculation process may be implemented using the following Equation (7).

[0065]

Number

[0066] The contrast threshold m related to JND t may be defined as a relative quantity. For example, the difference between L max and L min is divided by a specific luminance value, either L max or L min or L max and L min in the middle (for example, the average of L max and L min ). In some embodiments, m t is divided by a multiplier (for example, 2) of a specific luminance value, either L max and L min in the middle of the difference between L max and L min or L max and L min . When quantizing luminance values in the GSDF into a plurality of gray levels, L max and L min may refer to adjacent gray levels among the plurality of gray levels. As a result, L j may be related to L t and L j-1 and L j+1 through m

[0067] In alternative embodiments, instead of the linear expressions as shown in Equation (7), non-linear expressions may be used to relate the JND or contrast threshold to the gray level. For example, instead of the simple ratio for the contrast threshold shown above, an alternative expression based on dividing the standard deviation by the mean may be used.

[0068] In some embodiments, the reference GSDF covers a range from 0 to 12,000 cd / m with digital code values represented as 12-bit integer values. 2 To further improve the accuracy of the reference GSDF, it may be multiplied by a fraction value f. Further, note that the central digital value L2048 (the digital code value is limited to 0 and 4096 at least as in a 12-bit signed space compatible with SDI) may be mapped to 100 cd / m. t Equation (7) may give the following Equation (8). 2

[0069]

Number

[0070] FIG. 3 shows an exemplary GSDF that maps between a plurality of gray levels (in logarithmic luminance values) and a plurality of digital code values in a 12-bit code space, based on an exemplary embodiment of the present invention.

[0071] ​​FIG. 4 shows a curve depicting the Weber ratio (delta L / L or ΔL / L) based on the exemplary GSDF gray levels of FIG. 3. The perceptual non-linearity of human vision shown in FIG. 4 is represented as a function of luminance values on a logarithmic luminance axis. A comparable visual difference (e.g., JND) in human vision corresponds to a larger delta L / L value at lower luminance values. The curve of the Weber ratio asymptotes to a constant value (e.g., a Weber ratio of 0.002 where Weber's law is satisfied at higher luminance values) for higher luminance values.

[0072] 〈7. Functional Model〉 To obtain the mapping between digital code values and gray levels in the GSDF (reference GSDF or device-specific GSDF) described in this document, one or more analytical functions may be used. The one or more analytical functions may be unique, standard-based, or an expression from a standard-based function. In some embodiments, a GSDF generator (e.g., 504 in FIG. 5) may generate a GSDF in the form of one or more forward look-up tables (LUTs) and / or one or more inverse LUTs based on the one or more analytical functions (or formulas). At least some of these LUTs may be provided to a variety of image data codecs (e.g., 506 in FIG. 5) or a wide variety of display devices for use in converting between reference gray levels and reference digital code levels for the purpose of encoding reference image data. Additionally, optionally, or alternatively, at least some of the analytical functions (where the coefficients are in integer or floating-point representation) may be provided directly to an image data codec or a wide variety of display devices for use in obtaining the mapping between digital code values and gray levels in the GSDF described in this document and / or in performing the conversion between gray levels and digital code levels for the purpose of encoding image data.

[0073] In some embodiments, the analytical functions described in this document may have an ascending function that can be used to predict digital code values based on the corresponding gray levels, as follows.

[0074]

Number

[0075] In some embodiments, the analytical function is the inverse function corresponding to the ascending function of Equation (9) and may be used to predict the luminance value based on the corresponding digital code value, as follows.

[0076]

Number

[0077] Similarly, the luminance value predicted based on a plurality of digital code values using Equation (10) may be compared with the observed luminance value. The observed luminance value may be generated, but is not limited to, using numerical calculations based on a CSF model as discussed above or using experimental data of human vision. In one embodiment, the deviation between the predicted luminance value and the observed luminance value may be derived as a function of the parameters n, m, c1, c2, and c3, and this deviation may be minimized to derive the optimal values of the parameters n, m, c1, c2, and c3 in Equation (10).

[0078] The set of optimal values of the parameters n, m, c1, c2, and c3 determined using Equation (9) may or may not be the same as the set of optimal values of the parameters n, m, c1, c2, and c3 determined using Equation (10). If there is a difference between the two sets, one or both of the two sets may be used to generate the mapping between the digital code value and the luminance value. In some embodiments, the two sets of optimal values of the parameters n, m, c1, c2, and c3, if different, may be reconciled based on the minimization of the round trip error introduced, for example, by performing the forward and inverse encoding operations by both Equations (9) and (10). In some embodiments, the error resulting as a result of multiple round trips in the digital code value and / or the luminance value or gray level may be examined. In some embodiments, the selection of the parameters in Equations (9) and (10) may be based at least in part on the criterion that no significant error occurs in one round trip, two round trips, or more. Examples of significant round trip errors may include, but are not limited to, errors smaller than 0.0001%, 0.001%, 0.01%, 0.1%, 1%, 2%, or other configurable values.

[0079] The embodiments include using a sign space of one of one or more different bit lengths to represent digital control values. Optimized values of the parameters in equations (9) and (10) may be obtained for each of the plurality of sign spaces. Here, each sign space has a different one of one or more different bit lengths. Based on the optimized values of equations (9) and (10), a distribution of sign errors (e.g., a forward conversion error, an inverse conversion error, or a round-trip error in a digital sign value based on equations (9) and (10)) may be determined. In some embodiments, a numerical difference of 1 in two digital sign values corresponds to a contrast threshold at the light level between the two luminance values represented by those two digital sign values (or corresponds to the JND). FIG. 10A shows the maximum of the sign errors in JND units in a plurality of sign spaces, each having a different one of one or more different precisions (having different bit lengths), based on some exemplary embodiments. For example, based on the function model described herein, the maximum sign error for a sign space of infinite or unlimited bit length is 11.252. In contrast, based on the function model described herein, the maximum sign error for a sign space of 12-bit length (or 4096) is 11.298. This indicates that a 12-bit length sign space for digital sign values is an excellent choice in the function model represented by equations (9) and (10).

[0080] FIG. 10B shows the distribution of sign errors for a 12-bit length (or 4096) sign space by forward conversion (from luminance value to digital sign value) specified by equation (9), based on an exemplary embodiment. FIG. 10C shows the distribution of sign errors for a 12-bit length (or 4096) sign space by inverse conversion (from digital sign value to luminance value) specified by equation (10), based on an exemplary embodiment. Both FIG. 10B and FIG. 10C show a maximum sign error less than 12.5.

[0081] Figure 11 shows the values of parameters that can be used in equations (9) and (10) based on an exemplary embodiment. In some embodiments, as shown in the figure, integer-based formulas are used to represent / approximate these non-integer values in the specific implementation of the function model described in this document. In some other embodiments, fixed-point or floating-point values with one of one or more precisions (e.g., 14-, 16-, or 32-bit) may be used to represent / approximate these non-integer values in the specific implementation of the function model described in this document.

[0082] Embodiments include using a function model based on a formula other than those given in equations (9) and (10) (which may be a tone mapping curve). For example, a cone model based on the following Naka-Rushton formula may be used by the function model described in this document.

[0083]

Equation

[0084] In another example, the function model may be generated by the following Raised mu formula.

[0085]

Equation

[0086] In the usage in this manuscript, in some embodiments, a function model can be used to predict a sign value from a luminance value or to predict a luminance value from a sign value. The formula used by the function model may be reversible. The same or similar processing logic may be implemented to perform forward and inverse conversions between these values. In some embodiments, model parameters including but not limited to any exponent may be expressed by a fixed-point value or an integer-based formula. Thus, at least a part of the processing logic can be efficiently implemented in only hardware, only software, or a combination of hardware and software. Similarly, at least a part of the LUT generated by the function model or the model formula (such as formulas (9) to (12)) can be efficiently implemented in only hardware, only software, or a combination of hardware and software (including ASIC or FPGA). In some embodiments, one, two, or more function models may be implemented in a single computing device, a configuration consisting of multiple computing devices, a server, etc. In some embodiments, the error of the predicted sign value may be within 14 sign values of the target value or the observed value over the full range of the visible dynamic range of the luminance value. In some embodiments, this holds for both forward and inverse conversions. The same or different sets of model parameters may be used in forward and inverse conversions. The round-trip accuracy can be maximized with the optimal values of the model parameters. Various sign spaces can be used. In an individual embodiment, a 12-bit long (4096) sign space may be used to accept digital sign values with a minimum sign error over the full range of the visible dynamic range.

[0087] In the usage in this document, the reference GSDF may refer to the reference digital code values and reference gray levels associated under a function model determined numerically based on the CSF model (for example, without determining any functional representation of the mapping between digital code values and luminance values), or determined from data from human vision research (the model parameters of which can be determined with target or observed values under the CSF model). In some embodiments, the device GSDF may also have a mapping between digital code values and gray levels that can be analytically represented by the function models described in this document.

[0088] 〈8. Image Data Exchange Based on Reference GSDF〉 For illustrative purposes, it has been described that digital code values exist in a 12-bit code space. However, the present invention is not limited thereto. Digital code values with different code spaces (for example, bit depths different from 12 bits) may be used in the reference GSDF. For example, 10-bit integer values may be used to represent digital codes. Instead of mapping the digital code value 4076 to the luminance value 12000 cd / m 2 in the 12-bit representation of the digital code, in the 10-bit representation of the digital code, the digital code value 1019 may be mapped to the luminance value 12000 cd / m 2 Thus, these and other variations in the code space (bit depth) may be used for digital code values in the reference GSDF.

[0089] The reference GSDF may be used to exchange image data across different GSDFs that may be individually designed for each type of image acquisition device or image rendering device. For example, the GSDF implemented with a particular type of image acquisition device or image rendering device may implicitly or explicitly depend on model parameters that do not match the model parameters of the standard GSDF or the device-specific GSDF in another type of image acquisition device or image rendering device.

[0090] The reference GSDF may correspond to the curve shapes depicted in FIGS. 3 and 4. Generally, the shape of the GSDF depends on the parameters used to derive or design the GSDF. Thus, the reference GSDF depends on the reference CSF model and the reference model parameters used to generate the reference GSDF from the reference CSF model. The curve shape of the device-specific GSDF depends on the specific device, and if the specific device is a display, it includes display parameters and viewing conditions.

[0091] In one example, a display limited to a range of supported luminance values less than 500 cd / m 2 may not experience the increase in slope in the high luminance value region as shown in FIG. 3 (which occurs when human vision shifts to a logarithmic behavior for all frequencies). Driving this display with the curve shape of FIG. 3 may lead to a suboptimal (e.g., worse than optimal) gray level assignment, where there may be too many gray levels assigned to bright regions and insufficient gray levels assigned to dark regions.

[0092] In another example, a low contrast display is designed to be used outdoors under various daylight conditions. The luminance range of this display may appear almost, or almost completely, in the logarithmic behavior region of FIG. 3. Driving this low contrast display with the curve shape of FIG. 3 may also lead to a suboptimal (worse than optimal) gray level assignment, where there may be too many gray levels assigned to dark regions and insufficient gray levels assigned to bright regions.

[0093] Under the techniques described in this document, each display may use its own GSDF (which depends not only on the display parameters but also on viewing conditions that affect the actual black level, for example) to optimally support the perceptual information in the image data encoded with the reference GSDF. The reference GSDF is used by one or more upstream (e.g., encoding) devices for the overall encoding of the image data in order to preserve as much perceptual detail as possible. The image data encoded with the reference GSDF is then delivered to one or more downstream (e.g., decoding) devices. In one exemplary embodiment, the encoding of the image data based on the reference GSDF is independent of the particular device that will later decode and / or render the image data.

[0094] Each device (e.g., a display) has its own GSDF that supports / optimizes the device-specific gray levels. The device-specific gray levels may be known to the display manufacturer or may be individually designed by the manufacturer to support a device-specific GSDF (which may or may not be standard-based). The line driver of the device may be implemented with quantized luminance values specific to the device. For the device, optimization may best be made based on the quantized luminance values specific to the device. Further, the dark black level (e.g., the lowest device-specific gray level) that can be used as the lower limit of the range of device-specific gray levels may be set, in part, based on the ambient light level and / or the light reflectivity of the device (which may be known to the manufacturer). Once the dark black level is set in this way, the device-specific gray levels may be obtained or set by implicitly or explicitly accumulating (e.g., integrating) the quantization bins in the line driver of the device. The derivation and / or adjustment of the gray levels may or may not be done at runtime when the device is rendering images in parallel.

[0095] Thus, under the techniques described in this document, embodiments of the present invention may include, but are not limited to, encoding image data using a reference GSDF and decoding and rendering the image data using a display-specific GSDF.

[0096] The techniques described in this document may be used to exchange image data across a variety of devices with different GSDFs. FIG. 5 shows an exemplary framework (500) for exchanging image data with devices of different GSDFs, based on an exemplary embodiment of the present invention. As shown in FIG. 5, an adaptive CSF model (502) may be used to generate a reference GSDF (504). The term "adaptive" may refer to the ability of the CSF model to adapt to the non-linearity and behavior of human vision. The adaptive CSF model may be constructed, at least in part, based on a plurality of CSF parameters (or model parameters). The plurality of model parameters may include, for example, a light adaptation level, a display area in degrees of width, a noise level, a perspective adjustment (physical viewing distance), a luminance, or a color modulation vector (which may be related, for example, to a test image or image pattern used in the adaptive CSF model (502)).

[0097] An upstream (e.g., encoding) device may receive image data to be encoded using a reference GSDF (504) before the image data or a derivative thereof is transmitted or delivered to a downstream (e.g., decoding) device. The image data to be encoded may initially be in any of a plurality of formats (standard-based, proprietary, its extensions, etc.) and / or may be derived from any of a plurality of image sources (cameras, image servers, tangible media, etc.). Examples of the image data to be encoded include, but are not limited to, raw or other high bit-depth image(s) 530. The raw or high bit-depth image may be derived from a camera, a studio system, an art director system, another upstream image processing system, an image server, a content database, etc. The image data may include, but is not limited to, digital photographs, video image frames, 3D images, non-3D images, computer-generated graphics, etc. The image data may include scene-based images, device-based images, or images having various dynamic ranges. Examples of the image data to be encoded include a high-quality version of the original image that is to be edited, downsampled, and / or compressed and, together with metadata, made into an encoded bitstream for delivery to an image receiving system (a downstream image processing system such as displays from various manufacturers). The raw or other high bit-depth image may be of a high sampling rate used by professionals, art studios, broadcasters, high-end media production entities, etc. The image data to be encoded may be fully or partially computer-generated or, furthermore, may be fully or partially obtained from existing image sources such as old movies and documentaries.

[0098] In the usage in this document, the phrase "image data to be encoded" may refer to the image data of one or more images. The image data to be encoded may include floating-point or fixed-point image data and may be in any color space. In one exemplary embodiment, the one or more images may be in the RGB color space. In another exemplary embodiment, the one or more images may be in the YUV color space. In one example, each pixel in the images described in this document has floating-point pixel values for all channels defined in the color space (e.g., the red, green, and blue color channels in the RGB color space). In another example, each pixel in the images described in this document has fixed-point pixel values (e.g., 16-bit or more / less bit fixed-point pixel values for the red, green, and blue color channels in the RGB color space) for all channels defined in the color space. Optionally and / or alternatively, each pixel may have downsampled pixel values for one or more of the channels in the color space.

[0099] In some embodiments, in response to receiving the image data to be encoded, an upstream device in the framework (500) maps the luminance value specified by or determined from the image data to a reference digital code value in the reference GSDF and generates reference encoded image data encoded using the reference digital code value based on the image data to be encoded. The mapping operation from the luminance value based on the image data to be encoded to the reference digital code value may include selecting a reference digital code value such that the corresponding reference gray level (such as those shown in Table 1) closely matches or approximates the luminance value specified by or determined from the image data to be encoded compared to any other reference luminance value in the reference GSDF, and replacing the luminance value with the reference digital code value in the reference encoded image data.

[0100] Additionally, optionally or alternatively, pre-processing and post-processing steps (which may include, but are not limited to, color space conversion, downsampling, upsampling, tone mapping, color grading, decompression, compression, etc.) may be performed as part of generating the reference-encoded image data.

[0101] In one exemplary embodiment, the framework (500) may have software and / or hardware components (such as an encoding or formatting unit (506)) configured to encode and / or format the reference-encoded image data into one or more encoded bitstreams or image files. The encoded bitstream or image file may be in a standard-based format, a proprietary format, or an extended format based at least in part on a standard-based format. Additionally and / or optionally, the encoded bitstream or image file may have metadata including one or more of the reference GSDF used to generate the reference-encoded image data, relationship parameters related to pre-processing or post-processing (such as model parameters; minimum luminance value, maximum luminance value, minimum digital code value, maximum digital code value, etc. as shown in Table 1, FIGS. 3 and 4; an identification field identifying a certain CSF among a plurality of CSFs; reference viewing distance).

[0102] In some embodiments, the framework (500) may have one or more separate upstream devices. For example, at least one of the one or more upstream devices in the framework (500) may be configured to encode image data based on a reference GSDF. The upstream device may have software and / or hardware components configured to perform the functions associated with 502, 504, and 506 in FIG. 5. The encoded bitstream or image file may be output by the upstream device (502, 504, and 506 in FIG. 5) through a network connection, digital interface, tangible storage medium, etc., and delivered in an image data flow (508) to another image processing device for processing or rendering.

[0103] In some exemplary embodiments, the framework (500) further has one or more downstream devices as one or more separate devices. The downstream device may be configured to receive / access the encoded bitstream or image file output by the one or more upstream devices from the image data flow (508). For example, the downstream device may have software and / or hardware components (such as a decode or reformat unit (510)) configured to decode and / or reformat the encoded bitstream or image file and restore / obtain the reference-encoded image data therein. As shown in FIG. 5, the downstream device may have a variety of display device sets.

[0104] In some embodiments, a display device (not shown) may be designed and / or implemented to support a reference GSDF. If the display device supports all gray levels in the reference GSDF, high-precision HDR image rendering may be provided. The display device may render an image at a level of detail finer than or the same as that detectable by human vision.

[0105] In some embodiments, the native digital code value of the display device in the device-specific GSDF (which may be implemented as a digitized voltage value in the display system, such as a digital drive level or DDL) may correspond to a device-specific gray level (or luminance value) that is different from that of the reference GSDF. The device-specific gray levels may be designed to support other standards, including those using sRGB, Rec. 709, or representations related to complementary densities. Additionally, optionally, or alternatively, the device-specific gray levels may be based on the inherent DAC characteristics of the display drive.

[0106] In some embodiments, display device A (512 - A) may be designed and / or implemented to support a device-specific GSDF A (514 - A) of a visible dynamic range (VDR) display. GSDF A (514 - A) may be based on a 12-bit bit depth (12-bit code space) for the device-specific digital code value, a contrast ratio (CR) of 10,000:1, and a >P3 color gamut. GSDF A (514 - A) may support gray levels within a first partial range (e.g., from 0 to 5,000 cd / m 2 ) within the entire range of the reference GSDF (504). Alternatively or optionally, GSDF A (514 - A) may support the entire range within the reference GSDF (504) (e.g., from 0 to 12,000 cd / m 2 ), but may have fewer reference gray levels than all of the reference GSDF (504).

[0107] In some embodiments, display device B (512-B) may be designed and / or implemented to support a device-specific GSDF B (514-B) for a dynamic range narrower than that of the VDR. For example, display device B (512-B) may be a standard dynamic range (SDR) display. In the usage in this document, the terms "standard dynamic range" and "low dynamic range" and / or their corresponding abbreviations "SDR" and "LDR" may be used synonymously and / or interchangeably. In some embodiments, GSDF B (514-B) may support an 8-bit bit depth for device-specific digital code values, a contrast ratio (CR) of 500-5,000:1, and a color gamut defined in Rec.709. In some embodiments, GSDF B (514-B) may provide gray levels within a second partial range of the reference GSDF (504) (e.g., from 0 to 2,000 cd / m 2 ).

[0108] In some embodiments, display device C (512-C) may be designed and / or implemented to support a device-specific GSDF C (514-C) for a dynamic range even narrower than that of the SDR. For example, display device C (512-C) may be a tablet display. In some embodiments, GSDF C (514-C) may support an 8-bit bit depth for device-specific digital code values, a contrast ratio (CR) of 100-800:1, and a smaller color gamut than that defined in Rec.709. In some embodiments, GSDF C (514-C) may provide gray levels within a third partial range of the reference GSDF (504) (e.g., from 0 to 1,200 cd / m 2 ).

[0109] In some embodiments, a display device (e.g., display device D(512-D)) may be designed and / or implemented to support a device-specific GSDF (e.g., GSDF D(514-D)) with a very limited dynamic range that is much narrower than SDR. For example, display device D(512-D) may be an electronic paper display. In some embodiments, GSDF D(514-D) may support a bit depth of 6 bits or less, a contrast ratio (CR) of 10:1 or less, and a color gamut that is much smaller than that defined in Rec.709 for device-specific digital code values. In some embodiments, GSDF D(514-D) may support gray levels within a fourth partial range of the reference GSDF(504) (e.g., from 0 to 100 cd / m 2 ).

[0110] The accuracy in image rendering can be gracefully scaled down for each of display devices A through D(512-A through -D). In some embodiments, a subset of the gray levels in each of the device-specific GSDFs A through D(514-A through -D) may be correlated or mapped to the supported reference gray levels in the reference GSDF(504) in such a way as to evenly distribute perceptible errors in the range of gray levels supported by that display device.

[0111] In some embodiments, a display device (e.g., one of 512-A through -D) having a device-specific GSDF (e.g., one of 514-A through -D) receives / extracts reference-encoded image data encoded based on a reference GSDF. In response, the display device or a conversion unit (e.g., one of 516-A through -D) therein maps the reference digital code value specified in the reference-encoded image data to a device-specific digital code value native to the display device. This may be performed in one of several ways. In one example, mapping from the reference digital code value to the device-specific digital code value includes selecting a device-specific gray level (corresponding to the device-specific digital code value) that closely matches or approximates the reference gray level (corresponding to the reference digital code value) compared to any other device-specific gray level. In another example, mapping from the reference digital code value to the device-specific digital code value includes (1) determining a tone-mapped luminance value based on the reference gray level (corresponding to the reference digital code value) associated with the reference GSDF, and (2) selecting a device-specific gray level (corresponding to the device-specific digital code value) that closely matches or approximates the tone-mapped luminance value compared to any other device-specific gray level.

[0112] Thereafter, the display device or a driver chip (e.g., one of 518-A through -D) therein may use the device-specific digital code value to render an image using the device-specific gray level corresponding to the display-specific code value.

[0113] Generally, the reference GSDF may be based on a CSF model that is different from the one that serves as the basis for the display-specific GSDF. A conversion / mapping between the reference GSDF and the device-specific GSDF is required. Even if the same CSF model is used to generate both the reference GSDF and the device-specific GSDF, different values of the model parameters may be used when deriving those GSDFs. For the reference GSDF, the model parameter values may be conservatively set to preserve details for a wide variety of downstream devices, while for the device-specific GSDF, the model parameter values may reflect the specific design / implementation and the viewing conditions when the display device renders an image. Since the viewing condition parameters of a specific display device (e.g., ambient light level, light reflectance ability of the display device, etc.) are different from the model parameter values used to derive the reference GSDF, a conversion / mapping between the reference GSDF and the device-specific GSDF is still necessary. Here, the viewing condition parameters may affect the display quality (e.g., contrast ratio, etc.) and may include those that increase the black level (e.g., the lowest gray level, etc.). The conversion / mapping between the reference GSDF and the device-specific GSDF under the techniques described in this paper improves the quality in image rendering (e.g., improving the contrast ratio by increasing the luminance value in the region of high values, etc.).

[0114] 〈9. Conversion of the Referenced Encoded Image Data〉 FIG. 6 shows an exemplary conversion unit (e.g., 516) according to some embodiments of the present invention. The conversion unit (516) may be one (e.g., 516-A) of the plurality of conversion units (e.g., 516-A to D) shown in FIG. 5, but is not limited thereto. In some embodiments, the conversion unit (516) may receive first definition data for the reference GSDF (REF GSDF) and second definition data for the device-specific GSDF (e.g., GSDF-A (514-A in FIG. 5)). In the usage in this document, “device-specific” and “display-specific” may be used interchangeably when the device is a display.

[0115] Based on the received definition data, the conversion unit (516) forms a conversion look-up table (conversion LUT) by cascading the reference GSDF with the display-specific GSDF. The cascading between the two GSDFs may include comparing the gray levels in the two GSDFs and establishing a mapping between the reference digital code value in the reference GSDF and the display-specific digital code value in the display-specific GSDF based on the result of the gray level comparison.

[0116] More specifically, when a reference digital code value in the reference GSDF is provided, the corresponding reference gray level may be determined based on the reference GSDF. The reference gray level thus determined may be used to locate the device-specific gray level in the display-specific GSDF. In one exemplary embodiment, the device-specific gray level to be located may match or approximate well with the reference gray level compared to any other display-specific gray level in the display-specific GSDF. In another exemplary embodiment, the tone-mapped luminance value may be obtained by a global or local tone-mapping operator acting on the reference gray level, and the device-specific gray level to be located may match or approximate well with the tone-mapped luminance value compared to any other display-specific gray level in the display-specific GSDF.

[0117] Using the device-specific gray level, the corresponding display-specific digital code value may be identified from the display-specific GSDF. In the conversion LUT, an entry consisting of the reference digital code value and the display-specific code value may be added or defined.

[0118] Each of the above steps may be repeated for other reference digital code values in the reference GSDF.

[0119] In some embodiments, the conversion LUT may be pre-constructed and stored before image data that is to be processed based at least in part on the conversion LUT is received and processed. In an alternative embodiment, the image data to be processed using the conversion LUT may be analyzed. The result of the analysis may be used to set up or at least adjust the correspondence between the reference digital code value and the device-specific digital code value. For example, if the image data exhibits a particular concentration or distribution of luminance values, the conversion LUT may be set up to preserve a large amount of detail in the region where the luminance values are concentrated.

[0120] In some embodiments, the conversion unit (516) has one or more software and / or hardware components (comparison subunit (602)) configured to compare the quantization pitches (e.g., the difference in luminance values or ΔL between adjacent digital code values) in both the reference GSDF and the display-specific GSDF (514-A). For example, the quantization pitch at a certain reference digital code value in the reference GSDF may be a reference luminance value difference (reference GSDF ΔL), while the quantization pitch at a certain display-specific digital code value in the display-specific GSDF may be a display-specific luminance value difference (display-specific GSDF ΔL). Here, the display-specific digital code value corresponds to (or is paired with) the reference digital code value. In some embodiments, the comparison subunit (602) compares these two luminance value differences. This process is essentially a test that can be performed based on the ΔL value or optionally and / or alternatively based on the relative slopes of the two GSDF curves.

[0121] The quantization step for the luminance value in the display-specific GSDF is typically larger than that of the reference GSDF. This is because one or more reference gray levels from the reference GSDF (such as corresponding to a high bit-depth region) are merged into the display-specific gray levels from the display-specific GSDF (such as corresponding to a low bit-depth region). In such cases, dithering is used to remove banding artifacts. As part of the overall dithering, dithering is also performed on the local surrounding output pixels (in space and / or time). In a sense, the human eye can be represented as a low-pass filter. At least in this sense, averaging the local surrounding pixels as described in this paper generates the desired output gray levels that reduce and / or remove the banding visual artifacts that would normally be present due to the large quantization steps in the display-specific GSDF.

[0122] In less common cases, the quantization step for the luminance value of the reference GSDF can sometimes be larger than that of the display-specific GSDF. A process based on a decontouring algorithm is used to synthesize the output gray levels based on the input gray levels, for example, by averaging neighboring input pixels.

[0123] Correspondingly, in the case of the "Y" path in FIG. 6 where the reference GSDF ΔL is greater than the display-specific GSDF ΔL, the decontouring algorithm flag is set for the entries in the conversion LUT having the reference digital code value and the display-specific digital code value.

[0124] In the case of the "N" path in FIG. 6 where the reference GSDF ΔL is less than the display-specific GSDF ΔL, the dither algorithm flag is set for the entries in the conversion LUT having the reference digital code value and the display-specific digital code value.

[0125] When the reference GSDF ΔL is equal to the display-specific GSDF ΔL, neither the contour removal algorithm flag nor the dither algorithm flag is set for the entry in the conversion LUT that has the reference digital code value and the display-specific digital code value.

[0126] The contour removal and dither algorithm flags may be stored together with the entry in the conversion LUT, or may be stored in a related data structure that is external to the conversion LUT but is operationally linked to the conversion LUT.

[0127] In some embodiments, the conversion unit (516) is configured to receive reference-encoded image data that may be in the form of a high-bit-depth or floating-point input image, and map the reference digital code value specified in the reference GSDF to the display-specific digital code value specified in the display-specific GSDF. In addition to mapping the digital code values between those GSDFs, the conversion unit (516) may be configured to perform contour removal or dithering based on the setting of the algorithm flags (contour removal algorithm flag or dither algorithm flag) discussed above.

[0128] As described above, the reference GSDF is likely to contain more detail than the display-specific GSDF. Thus, the "Y" path in FIG. 6 may not occur, or may occur less frequently. In some embodiments, the "Y" path and related processing may be omitted to simplify the implementation of the conversion unit.

[0129] In some embodiments, a reference digital code value determined for a pixel in the reference-encoded image data is provided, and the conversion unit (516) searches for a corresponding display-specific digital code value in the conversion LUT and replaces the reference digital code value with the corresponding display-specific digital code value. Additionally and / or optionally, the conversion unit (516) determines whether a contour removal or dithering algorithm should be executed for the pixel based on the presence / setting of an algorithm flag for an entry in the conversion LUT that includes the reference digital code value and the display-specific digital code value.

[0130] If it is determined that neither the contour removal algorithm nor the dithering algorithm should be executed (i.e., there is no instruction or flag for executing either algorithm), then contour removal and dithering are not performed on that pixel for the time being.

[0131] If it is determined that the contour removal algorithm should be executed, the conversion unit (516) may execute one or more contour removal algorithms (Decontour Algo.). Executing the one or more contour removal algorithms may include receiving image data of local neighboring pixels of the input and inputting the image data of the local neighboring pixels into the contour removal algorithm.

[0132] If it is determined that the dithering algorithm should be executed, the conversion unit (516) may execute one or more dithering algorithms (Dithering Algo.).

[0133] This pixel may still be involved in contour removal or dithering. This is the case when the conversion unit (516) determines that contour removal or dithering needs to be performed on neighboring pixels. In one example, the device-specific (output) gray level of the pixel may be used to dither local neighboring pixels. In another example, the reference (input) gray level of the pixel may be used to remove the contour of local neighboring pixels.

[0134] In some embodiments, the conversion unit (516) outputs the processing result of the above steps to a downstream processing unit or subunit. The processing result includes display-specific encoded image data in the format of an output image with a display-specific bit depth encoded with digital code values within a display-specific GSDF (e.g., GSDF-A).

[0135] FIG. 7 shows an exemplary SDR display (700) implementing 8-bit image processing. The SDR display (700) or the VDR decoding unit therein receives an encoded input. The encoded input includes image data reference-encoded within an image data container, which can be one of a plurality of image data container formats. The VDR decoding unit (702) decodes the encoded input and determines / retrieves the reference-encoded image data therefrom. The reference-encoded image data may have image data for individual pixels in a certain color space (e.g., RGB color space, YCbCr color space, etc.). The image data for individual pixels may be encoded with reference digital code values in the reference GSDF.

[0136] Additionally and / or optionally, the SDR display (700) has a display management unit (704) that maintains display parameters for the SDR display (700). The display parameters may at least in part define a display-specific GSDF (e.g., GSDF-B of FIG. 5) associated with the SDR display (700). The display parameters that define the display-specific GSDF may include the maximum (max) and minimum (min) gray levels supported by the SDR display (700). The display parameters may also include the primaries supported by the SDR display, the display size, the light reflectance of the image rendering surface of the SDR display, and the ambient light level. Some of the display parameters may be pre-configured with fixed values. Some of the display parameters may be measured by the SDR display (700) in real time or near real time. Some of the display parameters may be configurable by a user of the SDR display (700). Some of the display parameters may be pre-configured with default values and may be overwritten by measurement or by the user. The display management unit (704) may establish / shape the perceptual non-linearity of the display-specific gray levels based on a reference GSDF and, additionally and / or optionally, may perform tone mapping as part of establishing / shaping the display-specific gray levels. For example, a conversion LUT and / or other related metadata (e.g., dither and contour removal processing flags) as shown in FIG. 5 may be established by the display management unit (704) for the purpose of establishing / shaping the perceptual non-linearity of the display-specific gray levels based on the reference GSDF. A continuation of the processing as discussed above may be implemented using the display management unit (704) to generate a conversion LUT and / or other related metadata (712) related to one or both of the reference GSDF and the display-specific GSDF.The conversion LUT and / or other related metadata (712) may be accessed and used by other units or subunits within the SDR display (700). Additionally, the conversion LUT and / or other related metadata may be used as metadata (714) for inverting the perceptual non-linearity or for deriving such metadata. In the usage in this document, inverting the perceptual non-linearity may include converting the display-specific digital code values to display-specific digital drive levels (e.g., digitized voltage levels in a display device).

[0137] Additionally and / or optionally, the SDR display (700) includes a conversion unit (516) as shown in FIGS. 5 and 6 and an 8-bit perceptual quantizer (706). In some embodiments, the SDR display (700) or the conversion unit (516) and 8-bit perceptual quantizer (706) therein convert the reference-encoded image data to an output image of the display-specific bit depth encoded with display-specific digital code values associated with the display-specific GSDF (e.g., GSDF-A or GSDF-B in FIG. 5), and quantize the output image of the display-specific bit depth to perceptually-encoded image data in the 8-bit code space. In the usage in this document, the term "perceptually-encoded" may refer to a type of encoding based on a perceptual model of human vision such as the CSF underlying the reference GSDF.

[0138] Additionally and / or optionally, the SDR display (700) has a video post-processing unit (708) that can perform zero, one, or more, but not limited to, image processing operations on the perceptually-encoded image data in the 8-bit luminance representation. These image processing operations may include, but are not limited to, compression, decompression, color space conversion, downsampling, upsampling, or color grading. The results of these operations may be output to other parts of the SDR display (700).

[0139] In one exemplary embodiment, the SDR display (700) has an 8-bit inverse perceptual quantizer (710) configured to convert a display-specific digital code value resulting from an image processing operation into a display-specific digital drive level (e.g., a digitized voltage level). The display-specific digital drive level generated (or converted back from the digital code value) by the inverse perceptual quantizer (710) may support, among other things, one of several types of luminance non-linearities that can be supported in the SDR display (700). In one example, the inverse perceptual quantizer (710) converts the display-specific digital code value into a display-specific digital drive level that supports the luminance non-linearity associated with Rec.709. In another example, the inverse perceptual quantizer (710) converts the display-specific digital code value into a display-specific digital drive level that supports the luminance non-linearity associated with the linear luminance region or the logarithmic luminance region (which may be relatively easy to integrate with local dimming operations). In another example, the inverse perceptual quantizer (710) converts the display-specific digital code value into a display-specific digital drive level that has an optimal arrangement of display-specific gray levels for that particular display (700) and is potentially adjusted for the viewing conditions specific to that display (700) to support the display-specific CSF (or its associated GSDF).

[0140] 〈10. Exemplary Process Flow〉 FIG. 8A shows an exemplary process flow according to an embodiment of the present invention. In some embodiments, one or more computing devices or components, such as one or more computing devices within the framework (500), may execute this process flow. In block 802, the computing device receives image data to be encoded.

[0141] In block 804, the computing device encodes the image data to be encoded based on a reference mapping between a set of reference digital code values and a set of reference gray levels to obtain reference-encoded image data. Here, the luminance values in the image data to be encoded are represented by the set of reference digital code values. The luminance difference between two reference gray levels represented by two adjacent reference digital code values in the set of reference digital code values may be inversely proportional to the peak contrast sensitivity of the human vision adapted at a certain light level.

[0142] In block 806, the computing device outputs the reference-encoded image data.

[0143] In an embodiment, the computing device determines a reference gray scale display function (GSDF) based on a contrast sensitivity function (CSF). The reference GSDF specifies the reference mapping between the set of reference digital code values and the set of reference gray levels. The CSF model includes one or more model parameters, and the model parameters may include an angular size falling within one or more of the ranges from 25 degrees × 25 degrees to 30 degrees × 30 degrees, from 30 degrees × 30 degrees to 35 degrees × 35 degrees, from 35 degrees × 35 degrees to 40 degrees × 40 degrees, from 40 degrees × 40 degrees to 45 degrees × 45 degrees, or greater than 45 degrees × 45 degrees.

[0144] In one embodiment, the computing device assigns an intermediate luminance value within the range of luminance values supported by the set of reference gray levels to an intermediate digital code value in the code space that accommodates the set of reference digital code values, and derives a plurality of sub-mappings by performing one or more of integration or integral calculations. Each sub-mapping maps a reference digital code value in the set of reference digital code values to a reference gray level in the set of reference gray levels. The intermediate luminance value may be selected within a range including one or more of less than 50 nits, between 50 nits and 100 nits, between 100 nits and 500 nits, or 500 nits or more.

[0145] In one exemplary embodiment, the set of reference gray levels covers a dynamic range having an upper limit with values less than 500 nits, between 500 nits and 1000 nits, between 1000 nits and 5000 nits, between 5000 nits and 10000 nits, between 10000 nits and 15000 nits, or greater than 15000 nits.

[0146] In one embodiment, the peak contrast sensitivity is determined from a certain contrast sensitivity curve among a plurality of contrast sensitivity curves determined based on a contrast sensitivity function (CSF) model having model parameters including one or more of a luminance value variable, a spatial frequency variable, or one or more other variables.

[0147] In one embodiment, at least two peak contrast sensitivities determined based on at least two of the plurality of contrast sensitivity curves appear at two different spatial frequency values.

[0148] In one embodiment, the computing device converts one or more input images represented, received, transmitted, or stored using image data to be encoded from an input video signal into one or more output images represented, received, transmitted, or stored using reference encoded image data included in an output video signal.

[0149] In one embodiment, the image data to be encoded includes image data encoded in one of a high-resolution high-dynamic range (HDR) image format, an RGB color space related to the Academy Color Encoding Specification (ACES) of the Academy of Motion Picture Arts and Sciences (AMPAS), the P3 color space standard of the Digital Cinema Initiative, the Reference Input Medium Metric / Reference Output Medium Metric (RIMM / ROMM) standard, the sRGB color space, an RGB color space related to the ITU BT.709 recommendation standard, and the like.

[0150] In one embodiment, the luminance difference between two reference gray levels represented by two adjacent reference digital code values is less than the minimum perceptible difference threshold at that particular light level.

[0151] In an exemplary embodiment, the particular light level is a luminance value between (including both ends) the two luminance values.

[0152] In one embodiment, the set of reference digital code values has integer values in a code space having a bit depth of less than 12 bits; between 12 bits and 14 bits; at least 14 bits; 14 bits or more.

[0153] In some embodiments, the set of reference gray levels may have a set of quantized luminance values.

[0154] FIG. 8B shows another exemplary process flow according to an embodiment of the present invention. In some embodiments, one or more computing devices or components, such as one or more computing devices within the framework (500), may execute this process flow. In block 852, the computing device determines a digital code mapping between a set of reference digital code values and a set of device-specific digital code values. Here, the set of reference digital code values is mapped to a set of reference gray levels in the reference mapping, while the set of device-specific digital code values is mapped to a set of device-specific gray levels in the device-specific mapping.

[0155] In block 854, the computing device receives reference encoded image data encoded with the set of reference digital code values. The luminance values in the reference encoded image data are based on the set of reference digital code values. The luminance difference between two reference gray levels represented by two adjacent reference digital code values in the set of reference digital code values may be inversely proportional to the peak contrast sensitivity of human vision adapted at a particular light level.

[0156] In block 856, the computing device transcodes the reference encoded image data encoded with the set of reference digital code values into device-specific image data encoded with the device-specific digital control codes based on the digital code mapping. The luminance values in the device-specific image data are based on the set of device-specific digital code values.

[0157] In one embodiment, the computing device determines a set of correspondence relationships between the set of reference digital code values and the set of device-specific digital code values. Here, the correspondence relationships in the set of correspondence relationships associate the reference digital code values in the set of reference digital code values with the device-specific digital code values. The computing device further compares a first luminance difference in the reference digital code values with a second luminance difference in the device-specific digital code values, and stores an algorithm flag regarding whether dithering should be performed, contour removal should be performed, or no operation should be performed for the reference digital code values based on the comparison between the first luminance difference and the second luminance difference.

[0158] In one embodiment, the computing device determines a reference digital code value from reference encoded image data for a pixel, and further determines whether an algorithm flag is set for the reference digital code value. In response to determining that the algorithm flag is set for contour removal, the computing device executes a contour removal algorithm on the pixel. Alternatively, in response to determining that the algorithm flag is set for dithering, the computing device executes a dithering algorithm on the pixel.

[0159] In one embodiment, the computing device renders one or more images on a display based on device-specific image data encoded with the set of device-specific digital control codes. Here, the display may be, but is not limited to, one of a visible dynamic range (VDR) display, a standard dynamic range (SDR) display, a tablet computer display, or a handheld device display.

[0160] In one embodiment, a device-specific grayscale display function (GSDF) specifies a device-specific mapping between the set of device-specific digital code values and the set of device-specific gray levels.

[0161] In one embodiment, the device-specific mapping is derived based on one or more display parameters and zero or more viewing condition parameters.

[0162] In one embodiment, the set of device-specific gray levels covers a dynamic range having upper limits with values less than 100 nits, greater than or equal to 100 nits and less than 500 nits, between 500 nits and 1000 nits, between 1000 nits and 5000 nits, between 5000 nits and 10000 nits, or greater than 10000 nits.

[0163] In one embodiment, a computing device converts one or more input images represented, received, transmitted, or stored using reference-encoded image data from an input video signal into one or more output images represented, received, transmitted, or stored using device-specific image data included in an output video signal.

[0164] In one embodiment, the device-specific image data supports image rendering in one of a high-resolution high dynamic range (HDR) image format, an RGB color space related to the Academy Color Encoding Specification (ACES) of the Academy of Motion Picture Arts and Sciences (AMPAS), the P3 color space standard of the Digital Cinema Initiative, the Reference Input Medium Metric / Reference Output Medium Metric (RIMM / ROMM) standard, the sRGB color space, and an RGB color space related to the ITU BT.709 recommendation standard.

[0165] In one embodiment, the set of device-specific digital code values has integer values in a code space having a bit depth of 8 bits; more than 8 bits and less than 12 bits; or 12 bits or more.

[0166] In one embodiment, the set of device-specific gray levels may have a set of quantized luminance values.

[0167] In various embodiments, an encoder, a decoder, a system, etc. execute any or part of the methods described above.

[0168] 〈11. Implementation Mechanism - Overview of Hardware〉 According to one embodiment, the techniques described herein are implemented by one or more special-purpose computing devices. The special-purpose computing device may be fixedly configured to execute the techniques, or may include a digital electronic device that is persistently programmed to execute the techniques, such as one or more application specific integrated circuits (ASICs) or field programmable gate arrays (FPGAs), or may include one or more general-purpose hardware processors programmed to execute the techniques according to program instructions in firmware, memory, other storage, or a combination. Such special-purpose computing devices may combine custom fixed-configuration logic, ASICs, or FPGAs with custom programming to achieve the techniques. The special-purpose computing device may be a desktop computer system, a portable computer system, a handheld device, a networking device, or any other device that incorporates fixed-configuration and / or program logic for implementing the techniques.

[0169] For example, FIG. 9 is a block diagram illustrating a computer system 900 in which an exemplary embodiment of the invention may be implemented. Computer system 900 includes a bus 902 or other communication mechanism for communicating information, and a hardware processor 904 coupled to bus 902 for processing information. Hardware processor 904 may be, for example, a general-purpose microprocessor.

[0170] Computer system 900 also includes a main memory 906 coupled to bus 902 for storing information and instructions to be executed by processor 904, such as random access memory (RAM) or other dynamic storage devices. Main memory 906 may also be used to store temporary variables or other intermediate information during execution of instructions to be executed by processor 904. When such instructions are stored on a non-transitory storage medium accessible to processor 904, computer system 900 is customized into a special purpose machine that executes the processes specified in the instructions.

[0171] Computer system 900 further includes a read only memory (ROM) 908 or other static storage device coupled to bus 902 for storing static information and instructions for processor 904. A storage device 910, such as a magnetic disk or optical disk, is provided and coupled to bus 902 for storing information and instructions.

[0172] Computer system 900 may be coupled via bus 902 to a display 912, such as a liquid crystal display, for displaying information to a computer user. An input device 914, including alphanumeric and other keys, is coupled to bus 902 for communicating information and command selections to processor 904. Another type of user input device is a cursor control 916, such as a mouse, trackball, or cursor direction keys, for communicating direction information and command selections to processor 904 and for controlling cursor movement on display 912. This input device typically has two degrees of freedom in two axis directions, for example, a first axis (e.g., x) and a second axis (e.g., y), thereby enabling the device to specify a position in a plane.

[0173] Computer system 900 may use customized fixed configuration logic, one or more ASICs or FPGAs, firmware and / or program logic combined with the computer system to make or program computer system 900 into a special purpose machine to implement the techniques described in this paper. According to certain embodiments, the techniques herein are performed by computer system 900 in response to a processor 904 executing one or more sequences of one or more instructions included in main memory 906. Such instructions may be read into main memory 906 from another storage medium such as storage device 910. Execution of the sequence of instructions included in main memory 906 causes processor 904 to perform the process steps described herein. In alternative embodiments, fixed configuration circuitry may be used instead of or in combination with software instructions.

[0174] As used herein, the term "storage medium" refers to any non-transitory medium that stores data and / or instructions that operate a machine in a specific manner. Such storage media may include non-volatile media and / or volatile media. Non-volatile media includes, for example, optical or magnetic disks such as storage device 910. Volatile media includes dynamic memory such as main memory 906. Common forms of storage media include, for example, floppy disks, flexible disks, hard disk drives, semiconductor drives, magnetic tape or any other magnetic data storage media, CD-ROM, any other optical data storage media, any physical media with patterns of holes, RAM, PROM and EPROM, flash EPROM, NVRAM, any other memory chip or cartridge.

[0175] A memory medium is different from, but may be used in association with, a transmission medium. The transmission medium participates in transferring information between memory media. For example, the transmission medium includes coaxial cables, copper wire, and fiber optics, including the wires that form bus 902. The transmission medium can also take the form of acoustic or light waves such as those generated during radio wave and infrared data communications.

[0176] Various forms of media may be involved in carrying one or more sequences of one or more instructions to processor 904 for execution. For example, the instructions may initially be carried on a magnetic disk or semiconductor drive of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions through a telephone line using a modem. A modem local to computer system 900 can receive the data on the telephone line and convert the data into an infrared signal using an infrared transmitter. An infrared detector can receive the data carried in the infrared signal, and appropriate circuitry can place the data on bus 902. Bus 902 carries the data to main memory 906, from which processor 904 fetches and executes the instructions. The instructions received by main memory 906 may optionally be stored on storage device 910 before or after execution by processor 904.

[0177] Computer system 900 also includes a communication interface 918 coupled to bus 902. Communication interface 918 provides a two-way data communication coupling to network link 920 that is connected to local network 922. For example, communication interface 918 may be an integrated services digital communication network (ISDN) card, cable modem, satellite modem, or modem to provide a data communication connection to a corresponding type of telephone line. As another example, communication interface 918 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. A wireless link may also be implemented. In any such implementation, communication interface 918 transmits and receives electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

[0178] Network link 920 typically provides data communication to other data devices through one or more networks. For example, network link 920 may provide a connection through local network 922 to data facilities operated by host computer 924 or Internet service provider (ISP) 926. ISP 926 provides data communication services through a worldwide packet data communication network commonly referred to as the "Internet" 928. Both local network 922 and Internet 928 use electrical, electromagnetic, or optical signals that carry digital data streams. Signals through various networks that carry digital data to / from computer system 900 and signals on network link 920 and through communication interface 918 are exemplary forms of transmission media.

[0179] Computer system 900 can send messages and receive data, including program code, through a network (singular or plural), network link 920, and communication interface 918. In the example of the Internet, server 930 may send the requested code for an application program through Internet 928, ISP 926, local network 922, and communication interface 918.

[0180] The received code may be executed by processor 904 when received and / or stored in storage device 910 or other non-volatile memory for later execution.

[0181] 〈12. Numbered Embodiments, Equivalents, Extensions, Alternatives, etc.〉 The numbered example embodiments (EEE: enumerated example embodiment) of the present invention have been described above in relation to image data exchange based on perceptual luminance non-linearity across displays of different functions. Thus, embodiments of the present invention may relate to one or more of the examples listed in Table 2 below.

[0182] Table 2 Numbered Embodiments 〔EEE1〕 Receiving the image data to be encoded; Encoding the received image data based on a reference mapping between a set of reference digital code values and a set of reference gray levels to obtain reference-encoded image data, wherein the luminance values in the received image data are represented by the set of reference digital code values, the luminance difference between two reference gray levels in the received image data is represented by two adjacent reference digital code values in the set of reference digital code values, and the luminance difference between two adjacent reference digital code values is inversely proportional to the peak contrast sensitivity of human vision adapted at a certain light level; Outputting the reference-encoded image data. Method [EEE2] The method according to EEE1, further comprising the step of determining a reference gray scale display function (GSDF) based on a contrast sensitivity function (CSF), wherein the reference GSDF specifies the reference mapping between the set of reference digital code values and the set of reference gray levels. [EEE3] The method according to EEE2, wherein the CSF model includes one or more model parameters, and the one or more model parameters fall within a range including one or more of between 25 degrees × 25 degrees and 30 degrees × 30 degrees, between 30 degrees × 30 degrees and 35 degrees × 35 degrees, between 35 degrees × 35 degrees and 40 degrees × 40 degrees, between 40 degrees × 40 degrees and 45 degrees × 45 degrees, or greater than 45 degrees × 45 degrees, and having an angular size. [EEE4] The method according to EEE1, comprising: assigning an intermediate luminance value within the range of luminance values supported by the set of reference gray levels to an intermediate digital code value in the code space accommodating the set of reference digital code values; and deriving a plurality of sub-mappings by performing one or more of integration or integral calculations, each sub-mapping mapping a reference digital code value in the set of reference digital code values to a reference gray level in the set of reference gray levels. Method [EEE5] The method according to EEE4, wherein the intermediate luminance value is selected within a range including one or more of less than 50 nits, between 50 nits and 100 nits, between 100 nits and 500 nits, or greater than 500 nits. [EEE6] The method according to EEE1, wherein the set of reference gray levels covers a dynamic range having an upper limit with values less than 500 nits, between 500 nits and 1000 nits, between 1000 nits and 5000 nits, between 5000 nits and 10000 nits, between 10000 nits and 15000 nits, or greater than 15000 nits. 〔EEE7〕 The method according to EEE1, wherein the peak contrast sensitivity is determined from a certain contrast sensitivity curve among a plurality of contrast sensitivity curves determined based on a contrast sensitivity function (CSF) model having model parameters including one or more of a luminance value variable, a spatial frequency variable, or one or more other variables. 〔EEE8〕 The method according to EEE7, wherein at least two peak contrast sensitivities determined based on at least two of the plurality of contrast sensitivity curves appear at two different spatial frequency values. 〔EEE9〕 The method according to EEE1, further comprising the step of converting one or more input images represented by, received, transmitted, or stored using the image data to be encoded from an input video signal into one or more output images represented by, received, transmitted, or stored using the reference encoded image data included in an output video signal. 〔EEE10〕 The method according to EEE1, wherein the image data to be encoded includes image data encoded in one of a high - resolution high - dynamic range (HDR) image format, an RGB color space related to the Academy Color Encoding Specification (ACES) standard of the Academy of Motion Picture Arts and Sciences (AMPAS), the P3 color space standard of the Digital Cinema Initiative, the Reference Input Medium Metric / Reference Output Medium Metric (RIMM / ROMM) standard, the sRGB color space, or an RGB color space related to the standard of Recommendation BT.709 of the International Telecommunication Union (ITU). 〔EEE11〕 The method according to EEE1, wherein a luminance difference between two reference gray levels represented by two adjacent reference digital code values is smaller than a minimum perceptible difference (JND) threshold at the specific light level. 〔EEE12〕 The method according to EEE1, wherein the specific light level is a luminance value between (including both ends) the two luminance values. 〔EEE13〕 The method according to EEE1, wherein the set of reference digital code values has integer values in a code space having a bit depth of less than 12 bits; between 12 bits and 14 bits; at least 14 bits; or 14 bits or more. 〔EEE14〕 The method according to EEE1, wherein the set of reference gray levels has a set of quantized luminance values. 〔EEE15〕 The method according to EEE1, wherein the reference GSDF is determined based on a function model that is at least partially represented using one or more functions. 〔EEE16〕 The method according to EEE15, wherein the function model has one or more model parameters, and the values of the model parameters are optimized by minimizing a deviation between a predicted code value and a target code value. 〔EEE17〕 Determining a digital code mapping between a set of reference digital code values and a set of device-specific digital code values, wherein the set of reference digital code values is mapped to a set of reference gray levels in a reference mapping, and the set of device-specific digital code values is mapped to a set of device-specific gray levels in a device-specific mapping; Receiving the reference-encoded image data encoded with the set of reference digital code values, wherein the luminance values in the reference-encoded image data are based on the set of reference digital code values, and the luminance difference between two reference gray levels represented by two adjacent reference digital code values in the set of reference digital code values is inversely proportional to the peak contrast sensitivity of the human vision adapted at a specific light level; Transcoding the reference-encoded image data encoded with the set of reference digital code values into device-specific image data encoded with the set of device-specific digital control code values based on the digital code mapping, wherein the luminance values in the device-specific image data are based on the set of device-specific digital code values, including: Method. 〔EEE18〕 The method according to EEE17, comprising: Determining a set of correspondence relationships between the set of reference digital code values and the set of device-specific digital code values, wherein the correspondence relationships in the set of correspondence relationships associate the reference digital code values in the set of reference digital code values with device-specific digital code values; Comparing a first luminance difference in the reference digital code values with a second luminance difference in the device-specific digital code values; Storing an algorithm flag regarding whether dithering should be performed, contour removal should be performed, or no operation should be performed for the reference digital code values based on the comparison between the first luminance difference and the second luminance difference. Method. 〔EEE19〕 Determining a reference digital code value from the reference-encoded image data for a certain pixel; Further comprising determining whether an algorithm flag is set for the reference digital code value. The method according to EEE17. 〔EEE20〕 The method described in EEE19, further comprising, in response to determining that an algorithm flag is set for contour removal, performing a contour removal algorithm on that pixel. 〔EEE21〕 The method described in EEE19, further comprising, in response to determining that an algorithm flag is set for dithering, performing a dithering algorithm on that pixel. 〔EEE22〕 The method described in EEE17, further comprising rendering one or more images on a display based on the device-specific image data encoded with the set of device-specific digital control codes, wherein the display is one of a visible dynamic range (VDR) display, a standard dynamic range (SDR) display, a tablet computer display, or a handheld device display. 〔EEE23〕 The method described in EEE17, wherein a device-specific grayscale display function (GSDF) specifies the device-specific mapping between the set of device-specific digital code values and the set of device-specific gray levels. 〔EEE24〕 The method described in EEE17, wherein the device-specific mapping is derived based on one or more display parameters and zero or more viewing condition parameters. 〔EEE25〕 The method described in EEE17, wherein the set of device-specific gray levels covers a dynamic range having an upper limit with values less than 100 nits, between 100 nits and less than 500 nits, between 500 nits and 1000 nits, between 1000 nits and 5000 nits, between 5000 nits and 10000 nits, or greater than 10000 nits. 〔EEE26〕 The method according to EEE17, further comprising the step of converting one or more input images represented by the reference encoded image data from the input video signal, which are received, transmitted, or stored, into one or more output images represented by the device-specific image data included in the output video signal, which are received, transmitted, or stored. 〔EEE27〕 The device-specific image data supports image rendering in one of a high-resolution high-dynamic range (HDR) image format, an RGB color space related to the Academy Color Encoding Specification (ACES) standard of the Academy of Motion Picture Arts and Sciences (AMPAS), a P3 color space standard of the Digital Cinema Initiative, a Reference Input Medium Metric / Reference Output Medium Metric (RIMM / ROMM) standard, an sRGB color space, and an RGB color space related to the ITU's BT.709 recommendation standard, according to the method described in EEE17. 〔EEE28〕 The luminance difference between two reference gray levels represented by two adjacent reference digital code values is less than the minimum perceptible difference threshold at the specific light level, according to the method described in EEE17. 〔EEE29〕 The specific light level is a luminance value between (including both ends) the two luminance values, according to the method described in EEE17. 〔EEE30〕 The set of device-specific digital code values has integer values in a code space with a bit depth of 8 bits; more than 8 bits and less than 12 bits; or 12 bits or more, according to the method described in EEE17. 〔EEE31〕 The set of device-specific gray levels has a set of quantized luminance values, according to the method described in EEE17. 〔EEE32〕 At least one of the reference mapping and the device-specific mapping is determined based on a function model represented at least partially by one or more functions, according to the method described in EEE17. 〔EEE33〕 The method according to EEE32, wherein the function model has one or more model parameters, and the values of the model parameters are optimized by minimizing the deviation between the predicted symbol value and the target symbol value. 〔EEE34〕 An encoder that executes the method according to any one of EEE1 to 16. 〔EEE35〕 A decoder that executes the method according to any one of EEE17 to 33. 〔EEE36〕 A system that executes the method according to any one of EEE1 to 33. 〔EEE37〕 A system having an encoder and a decoder, wherein the encoder: receiving the image data to be encoded; encoding the received image data based on a reference mapping between a set of reference digital symbol values and a set of reference gray levels to obtain reference-encoded image data, wherein the luminance value in the image data to be encoded is represented by the set of reference digital symbol values, and the luminance difference between two reference gray levels represented by two adjacent reference digital symbol values in the set of reference digital symbol values is inversely proportional to the peak contrast sensitivity of the human vision adapted at a specific light level; and outputting the reference-encoded image data, wherein the decoder: determining a digital symbol mapping between a set of reference digital symbol values and a set of device-specific digital symbol values, wherein the set of device-specific digital symbol values is mapped to a set of device-specific gray levels in a device-specific mapping; receiving the reference-encoded image data; Encoding the reference encoded image data encoded with the set of reference digital code values into device-specific image data encoded with the set of device-specific digital control codes based on the digital code mapping, wherein the luminance values in the device-specific image data are based on the set of device-specific digital code values, and performing the steps. System. 〔EEE38〕 An image decoder comprising: A mapping determiner that determines a digital code mapping between a set of reference digital code values and a set of device-specific digital code values, wherein the set of reference digital code values are mapped to a set of reference gray levels in a reference mapping, and the set of device-specific digital code values are mapped to a set of device-specific gray levels in a device-specific mapping; A receiver that receives the reference encoded image data encoded with the set of reference digital code values, wherein the luminance values in the reference encoded image data are based on the set of reference digital code values, and the luminance difference between two reference gray levels represented by two adjacent reference digital code values in the set of reference digital code values is inversely proportional to the peak contrast sensitivity of human vision adapted at a specific light level; A transcoder that transcodes the reference encoded image data encoded with the set of reference digital code values into device-specific image data encoded with the set of device-specific digital control codes based on the digital code mapping, wherein the luminance values in the device-specific image data are based on the set of device-specific digital code values. Decoder. 〔EEE39〕 The decoder according to EEE38, comprising: Determining a set of correspondence relationships between the set of reference digital code values and the set of device-specific digital code values, wherein the correspondence relationships in the set of correspondence relationships associate the reference digital code values in the set of reference digital code values with the device-specific digital code values; Comparing a first luminance difference in the reference digital code values with a second luminance difference in the device-specific digital code values; Based on the comparison of the first luminance difference and the second luminance difference, storing an algorithm flag, wherein the algorithm flag functions to flag whether dithering should be performed for the reference digital code value, whether contour removal should be performed, or whether no operation should be performed; Decoder. 〔EEE40〕 Determining a reference digital code value from the reference-encoded image data for a pixel; Further configured to execute determining whether an algorithm flag is set for the reference digital code value; The decoder according to EEE38. 〔EEE41〕 The decoder according to EEE40, further configured to execute a contour removal function for the pixel in response to determining that an algorithm flag for contour removal is set. 〔EEE42〕 The decoder according to EEE40, further configured to execute a dithering process for the pixel in response to determining that an algorithm flag for dithering is set. 〔EEE43〕 Further configured to perform a step of rendering one or more images on a display based on the device - specific image data encoded with the set of device - specific digital control codes, wherein the display is one of a visible dynamic range (VDR) display, a standard dynamic range (SDR) display, a tablet computer display, or a handheld device display, the decoder described in EEE38 〔EEE44〕 A decoder as described in EEE38, wherein a device - specific grayscale display function (GSDF) specifies the device - specific mapping between the set of device - specific digital code values and the set of device - specific gray levels. 〔EEE45〕 A decoder as described in EEE38, wherein the device - specific mapping is derived based on one or more display parameters and zero or more viewing condition parameters. 〔EEE46〕 A decoder as described in EEE38, wherein the set of device - specific gray levels spans a dynamic range with upper limits having values less than 100 nits, 100 nits or more and less than 500 nits, between 500 nits and 1000 nits, between 1000 nits and 5000 nits, between 5000 nits and 10000 nits, or more than 10000 nits (e.g., covering...). 〔EEE47〕 A decoder as described in EEE38, further having a converter that converts one or more input images represented by, received, transmitted, or stored reference - encoded image data from an input video signal into one or more output images represented by, received, transmitted, or stored device - specific image data included in an output video signal. 〔EEE48〕 The image data inherent to the device supports image rendering in one of a high-resolution, high-dynamic range (HDR) image format, an RGB color space related to the Academy Color Encoding Specification (ACES) standard of the Academy of Motion Picture Arts and Sciences (AMPAS), the P3 color space standard of the Digital Cinema Initiative, the Reference Input Medium Metric / Reference Output Medium Metric (RIMM / ROMM) standard, the sRGB color space, or an RGB color space related to the standard of Recommendation BT.709 of the International Telecommunication Union (ITU), and is a decoder as described in EEE38. 〔EEE49〕 The luminance difference between two reference gray levels represented by two adjacent reference digital code values is less than the Just Noticeable Difference (JND) threshold at the specific light level, and is a decoder as described in EEE38. 〔EEE50〕 The specific light level is a luminance value between (including both ends) the two luminance values, and is a decoder as described in EEE38. 〔EEE51〕 The set of device-inherent digital code values has integer values in a code space with a bit depth of 8 bits; more than 8 bits and less than 12 bits; or 12 bits or more, and is a decoder as described in EEE38. 〔EEE52〕 The set of device-inherent gray levels has a set of quantized luminance values, and is a decoder as described in EEE31. 〔EEE53〕 At least one of the reference mapping and the device-inherent mapping is determined based on a function model expressed at least partially using one or more functions, and is a decoder as described in EEE38. 〔EEE54〕 The function model has one or more model parameters, and the values of the model parameters are optimized by minimizing the deviation between the predicted code value and the target code value, and is a decoder as described in EEE53. 〔EEE55〕 A non-transitory computer-readable storage medium encoded and storing instructions that, when executed by a computer or its processor, cause, execute, or control the computer or the processor to perform, execute, or control a process of decoding an image, or program the same, wherein the image decoding process comprises: Determining a digital code mapping between a set of reference digital code values and a set of device-specific digital code values, wherein the set of reference digital code values is mapped to a set of reference gray levels in a reference mapping, and the set of device-specific digital code values is mapped to a set of device-specific gray levels in a device-specific mapping; Receiving reference-encoded image data encoded with the set of reference digital code values, wherein the luminance values in the reference-encoded image data are based on the set of reference digital code values, and the luminance difference between two adjacent reference gray levels represented by two adjacent reference digital code values in the set of reference digital code values is inversely proportional to the peak contrast sensitivity of human vision adapted at a specific light level; Transcoding the reference-encoded image data encoded with the set of reference digital code values into device-specific image data encoded with the set of device-specific digital control codes based on the digital code mapping, wherein luminance. 〔EEE56〕 Means for determining a digital code mapping between a set of reference digital code values and a set of device-specific digital code values, wherein the set of reference digital code values is mapped to a set of reference gray levels in a reference mapping, and the set of device-specific digital code values is mapped to a set of device-specific gray levels in a device-specific mapping; Means for receiving reference-encoded image data encoded with the set of reference digital code values, wherein the luminance values in the reference-encoded image data are based on the set of reference digital code values, and the luminance difference between two reference gray levels represented by two adjacent reference digital code values in the set of reference digital code values is inversely proportional to the peak contrast sensitivity of the human vision adapted at a certain light level; Means for transcoding the reference-encoded image data encoded with the set of reference digital code values into device-specific image data encoded with the set of device-specific digital control code values based on the digital code mapping, wherein the luminance values in the device-specific image data are based on the set of device-specific digital code values, having the means; Digital decoding system. 〔EEE57〕 A step of receiving reference-encoded image data encoded with reference code values, wherein the reference code values represent a set of reference gray levels, a first pair of adjacent gray levels in the set of gray levels is related to the first peak contrast sensitivity of the human vision adapted at a first light level, and a second pair of adjacent gray levels in the set of gray levels is related to the second peak contrast sensitivity of the human vision adapted at a second different light level; A step of accessing a code mapping between the reference code values and the device-specific code values, wherein the device-specific code values represent a set of device-specific gray levels; Including a step of transcoding the reference-encoded image data into device-specific image data encoded with the device-specific control code based on the code mapping. Method. 〔EEE58〕 The method according to EEE57, wherein the set of reference gray levels covers a dynamic range having an upper limit with values less than 500 nits, between 500 nits and 1000 nits, between 1000 nits and 5000 nits, between 5000 nits and 10000 nits, between 10000 nits and 15000 nits, or greater than 15000 nits. 〔EEE59〕 The method according to EEE57, wherein the set of reference gray levels is configured based on a human visual model that supports a field of view greater than 40 degrees. 〔EEE60〕 The method according to EEE57, wherein the set of reference gray levels is related to a variable spatial frequency lower than a cut-off spatial frequency. 〔EEE61〕 The method according to EEE57, wherein the symbol mapping is configured to evenly distribute perceptible errors in the dynamic range covered by the device-specific gray levels. 〔EEE62〕 The method according to EEE57, wherein a first luminance value difference of a first pair of adjacent gray levels in the set of gray levels is inversely related to the first peak contrast sensitivity by a certain multiplication constant, and a first luminance value difference of a second pair of adjacent gray levels is inversely related to the second peak contrast sensitivity by the same multiplication constant. 〔EEE63〕 The method according to EEE57, wherein the reference symbol value and the reference gray level represented by the reference symbol value have different numerical values. 〔EEE64〕 The method according to EEE57, wherein based on the symbol mapping, the step of transcoding the reference-encoded image data into device-specific image data encoded with the device-specific control symbol is: determining a first luminance value difference between two adjacent reference symbol values at a certain reference symbol value; and determining a second luminance value difference between two adjacent device-specific symbol values at the device-specific symbol value corresponding to the reference symbol value; Based on the comparison of the first luminance value difference and the second luminance value difference, applying one of a dither algorithm or a contour removal algorithm to at least one pixel in the device-specific image data, Method. 〔EEE65〕 An image processing apparatus comprising: A data receiver configured to receive reference-encoded image data having reference code values, wherein the reference-encoded image data is encoded by an external encoding system, the reference code values represent reference gray levels, and the reference gray levels are selected using a reference gray scale display function based on the perceptual non-linearity of the human visual system adapted to various spatial frequencies at various light levels, a data receiver; A data converter configured to access a code mapping between the reference code values and device-specific code values of the image processing apparatus, wherein the device-specific code values are configured to generate device-specific gray levels configured for the image processing apparatus, and the data converter is configured to transcoder the reference-encoded image data into device-specific image data encoded with the device-specific code values based on the code mapping, a data converter, The image processing apparatus is at least one of: a game machine, a television, a laptop computer, a desktop computer, a netbook computer, a computer workstation, a cellular radio phone, an electronic book reader, a point-of-sale terminal, and a computer kiosk. Image processing apparatus.

[0183] Table 3 below describes the calculation of a perceptual curve EOTF for converting digital video code values to absolute linear luminance levels in terms of display. Also included is the inverse OETF for converting absolute linear luminance to digital code values.

[0184] Table 3 Exemplary specifications for the perceptual curve EOTF Definition of exemplary formulas: D = Digital code value of the perceptual curve, SDI legal unsigned integer, 10 or 12 bits b = Number of bits per component in the digital signal representation, 10 or 12 V = Signal value of the normalized perceptual curve, 0 ≤ V ≤ 1 Y = Normalized luminance value, 0 ≤ Y ≤ 1 L = Absolute luminance value, 0 ≤ L ≤ 10,000 cd / m 2 Exemplary EOTF decoding formula

Equation

Equation

Equation

[0185] The following Table 4 shows exemplary values for 10 bits.

[0186] Table 4 Exemplary table of values for 10 bits

[0187]

Table 2

[0188]

Table 3

[0189]

Table 4

[0190]

Table 5

[0191]

Table 6

[0192]

Table 7

[0193]

Table 8

[0194]

Table 9

[0195]

Table 10

[0196]

Table 11

[0197]

Table 12

[0198] Some aspects will be described. 〔Aspect 1〕 An image processing apparatus comprising: A data receiver configured to receive reference-encoded image data having reference code values, wherein the reference-encoded image data is encoded by an external encoding system, the reference code values represent reference gray levels, and the reference gray levels are selected using a reference gray scale display function based on the perceptual non-linearity of human vision adapted to various spatial frequencies at various light levels; A data converter configured to access a code mapping between the reference code values and device-specific code values of the image processing apparatus, wherein the device-specific code values are configured to generate device-specific gray levels configured for the image processing apparatus, and the data converter is configured to transcode the reference-encoded image data into device-specific image data encoded with the device-specific code values based on the code mapping; An image processing apparatus. 〔Aspect 2〕 The image processing apparatus according to Aspect 1, which is a standard dynamic range display device. 〔Aspect 3〕 The image processing apparatus according to aspect 1, configured to support one of an intermediate horizontal angle size between 40 degrees and 25 degrees and a narrow horizontal angle size of 25 degrees or less. 〔Aspect 4〕 The image processing apparatus according to aspect 1, configured to support one of an intermediate viewing distance between 1.5 meters and 0.5 meters and a short viewing distance of 0.5 meters or less. 〔Aspect 5〕 Receiving reference-encoded image data encoded with a reference code value, wherein the reference code value represents a set of reference gray levels; Accessing a code mapping between the reference code value and a device-specific code value, wherein the device-specific code value represents a set of device-specific gray levels; Transcoding the reference-encoded image data into device-specific image data encoded with the device-specific control code based on the code mapping, wherein a first quantization step between successive reference gray levels of the set is related to the contrast sensitivity of human vision adapted to spatial frequency at a first light level. Method. 〔Aspect 6〕 The method according to aspect 5, wherein the first quantization step size is related to the peak contrast sensitivity of human vision adapted to spatial frequency with respect to the first light level. 〔Aspect 7〕 The method according to aspect 5, wherein the first quantization step size is smaller than the minimum perceptible difference threshold at the first light level. 〔Aspect 8〕 The method according to aspect 5, wherein a second quantization step is related to the contrast sensitivity of human vision adapted to spatial frequency at a second light level, and the first and second quantization step sizes are different. 〔Aspect 9〕 The method according to aspect 8, wherein the second quantization step size is related to the peak contrast sensitivity of human vision adapted to spatial frequency with respect to the first light level. 〔Aspect 10〕 The method according to aspect 8, wherein the first light level is smaller than the second light level, and the first dither size is larger than the second dither size. [Aspect 11] The method according to aspect 5, covering a dynamic range having an upper limit in which the set of reference gray levels has values between 1000 nits and 15000 nits.

Claims

1. 1. A method for generating a bitstream containing image data, the image data being at least in part ##EQU00013## is encoded with a digital code value D, which represents the normalized luminance Y, based on the inverse of the functional model V is a normalized value of the digital code value D, 0≦Y≦1, and 0≦V≦1; n, m, c 1 , c 2 , c 3 is a predetermined value, ##EQU14## That is, A method comprising:

2. 2. The method of claim 1, wherein b is a bit depth corresponding to a number of bits used to represent the digital code value D, and b is 10 bits or 12 bits.

Images