De-banding based on image statistical information in SDR to HDR conversion

Abstract

One embodiment provides a computer-implemented method that includes employing a decoloring process based on image statistics in a dynamic range conversion system that includes a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or an SDR to HDR inverse tone mapping (ITM) process. The computing device performs a de-banding process in post-processing during determination of the one or more initial ITM explicit curve coefficients. One or more parameters of a weighting function of one or more initial ITM explicit curve coefficients are used as one or more control nodes for balancing the decoloring banding effect and preserving local details.

Description

Technical Field

[0001] One or more embodiments relate generally to image tone mapping, and in particular, to balancing de-banding effects and preserving local details for a display. Background Art

[0002] Although the High Dynamic Range (HDR) standard has been commercially available since 2014, the end-to-end processing from capture, creation, distribution to display has only recently matured. As a result, most videos available today are still limited to Standard Dynamic Range (SDR), which has given rise to the need for SDR to HDR Inverse Tone Mapping (ITM) technology. ITM allows SDR content to be seamlessly mixed into HDR native products. Summary of the invention

[0003] Technical Solution

[0004] One embodiment provides a computer-implemented method, the method comprising: employing a de-banding process based on image statistics in a dynamic range conversion system, the dynamic range conversion system comprising: a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or an SDR to HDR inverse tone mapping (ITM) process. A computing device performs the de-banding process in post-processing during determination of one or more initial ITM explicit curve coefficients. One or more parameters of a weighting function of the one or more initial ITM explicit curve coefficients are used as one or more control nodes for balancing the de-banding effect and preserving local details.

[0005] One embodiment provides a processor-readable medium including a program that, when executed by a processor, performs a debanding process based on image statistics in a dynamic range conversion system including an HDR to SDR TM process or an SDR to HDR ITM process to balance debanding effects for a display and preserve local details. The debanding process is performed in post-processing during determination of one or more initial ITM explicit curve coefficients. One or more parameters of a weighting function of the one or more initial ITM explicit curve coefficients are used as one or more control nodes for balancing debanding effects and preserving local details.

[0006] One embodiment provides a device, the device comprising: a memory storing instructions; and at least one processor executing the instructions including a process, the process being configured to: employ a de-banding process based on image statistics in a dynamic range conversion system, the dynamic range conversion system comprising an HDR to SDR TM process or an SDR to HDR ITM process. The de-banding process is performed in post-processing during determination of one or more initial ITM explicit curve coefficients. One or more parameters of a weighting function of the one or more initial ITM explicit curve coefficients are used as one or more control nodes for balancing the de-banding effect and preserving local details.

[0007] These and other features, aspects, and advantages of one or more embodiments will become understood with reference to the following description, appended claims, and accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] For a more complete understanding of the features and advantages of the embodiments and the preferred mode of use, reference should be made to the following detailed description taken in conjunction with the accompanying drawings, in which:

[0009] Figure 1 An example of a standard dynamic range (SDR) to high dynamic range (HDR) inverse tone mapping (ITM) process is shown;

[0010] Figure 2 An example of enhanced color banding artifacts after brightness range expansion is shown;

[0011] Figure 3 A block diagram of an SDR to HDR conversion system including a de-banding process according to an embodiment is shown;

[0012] Figure 4 shows a flow chart of a de-banding process according to an embodiment;

[0013] Figure 5 shows an example scatter plot for images with different brightness and a graph for a linear interpolation function according to an embodiment;

[0014] Figure 6 shows an example scatter plot for images with different brightness and a graph for a linear interpolation function according to an embodiment;

[0015] Fig. 7A shows example graphs of functions with different parameters according to an embodiment;

[0016] Figure 7B shows example graphs of functions with different parameters according to an embodiment;

[0017] Fig. 8Ashows an inverse tone mapping (ITM) curve for comparing before and after tuning of an associated example dark image according to an embodiment;

[0018] Figure 8B shows an inverse tone mapping (ITM) curve for comparing before and after tuning of an associated example bright image according to an embodiment;

[0019] Figure 8C shows an inverse tone mapping (ITM) curve for comparing before and after tuning of an associated example midtone image according to an embodiment; and

[0020] Fig. 9 A process for balancing de-banding effects and preserving local details for a display is shown in accordance with an embodiment. DETAILED DESCRIPTION

[0021] The following description is made for the purpose of illustrating the general principles of one or more embodiments and is not meant to limit the inventive concept claimed herein. In addition, the specific features described herein may be used in combination with other described features in each of various possible combinations and arrangements. Unless otherwise specifically defined herein, all terms will be given their broadest possible interpretation, including the meanings implied in the specification and the meanings understood by those skilled in the art and / or the meanings defined in dictionaries, papers, etc.

[0022] A description of example embodiments is provided on the following pages. The text and drawings are provided as examples only to help the reader understand the disclosed technology. They are not intended to, nor are they to be interpreted as, limiting the scope of the disclosed technology in any way. Although embodiments and examples have been provided, it will be clear to those skilled in the art from the disclosure herein that changes may be made to the illustrated embodiments and examples without departing from the scope of the disclosed technology.

[0023] One or more embodiments relate generally to image tone mapping, and in particular, to balancing debanding effects and preserving local details for a display. One embodiment provides a computer-implemented method comprising: employing a debanding process based on image statistics in a dynamic range conversion system, the dynamic range conversion system comprising a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or an SDR to HDR inverse tone mapping (ITM) process. A computing device performs the debanding process in post-processing during determination of one or more initial ITM explicit curve coefficients. One or more parameters of a weighting function of the one or more initial ITM explicit curve coefficients are used as one or more control nodes for balancing the debanding effect and preserving local details. For example, the one or more initial ITM explicit curve coefficients may include polynomial curve coefficients. For example, the one or more initial ITM explicit curve coefficients may include Bezier curve coefficients.

[0024] In current publications and industry use, global schemes with independent pixel-by-pixel processing are the most computationally efficient choice with a compromised de-banding effect. Local context-based methods (such as filtering-based methods) can achieve good de-banding performance but usually sacrifice local details. In addition, the application of those context-dependent schemes is highly dependent on the available hardware computing resources.

[0025] In an embodiment, the disclosed technology provides a global de-color banding solution that can be easily embedded in current SDR to HDR conversion technology without changing the system structure. In one or more embodiments, the ITM curve is flattened to reduce the distance between adjacent color / brightness levels, thereby suppressing (hiding) color banding artifacts.

[0026] Since color banding artifacts are mostly noticeable in large and smooth areas (such as the sky), it is reasonable to assume that shadow (highlight) areas in an overall dark (bright) scene are more susceptible to color banding artifacts. Therefore, the color banding risk brightness range is determined based on the brightness statistics of the image in this scheme. In addition, mid-tone areas usually have more details to be protected, so only the lower and upper ends of the ITM curve are flattened in this scheme to suppress shadow color banding and highlight color banding, respectively. In addition, based on experimental observations, increasing (decreasing) the brightness of the image reduces highlight (shadow) color banding, so this scheme will flatten the ITM curve by boosting the upper end while suppressing the lower end.

[0027] In one or more embodiments, the disclosed technology provides a global de-banding scheme in SDR to HDR ITM based on image statistics. Unlike some methods, the disclosed technology can determine the brightness range that is susceptible to color banding artifacts. The disclosed technology can process all pixels globally based on brightness statistics. In this way, the disclosed technology achieves a pleasing balance without the heavy computational burden from some context-based schemes or the performance compromise caused by blind global processing. The de-banding scheme is used as a post-processing of the initial ITM explicit Bezier curve coefficients, so it can be naturally embedded in the SDR to HDR conversion platform without causing significant or any system structure changes. In an embodiment, the parameters designed for the weighting function of the ITM explicit Bezier curve coefficients can be used as a control node for the user to balance the de-banding effect and retain local details.

[0028] Figure 1 An example of an SDR to HDR ITM process 100 is shown. Process 100 includes SDR input 105, image statistics calculation 110, ITM curve generation 120, SDR linearization 130, ITM 140, color space conversion 150, and HDR output 106. A global scheme with independent pixel-by-pixel processing can be a promising and computationally efficient approach with a compromised de-banding effect. Local context-based methods (such as filtering-based methods) can achieve good de-banding performance, but typically sacrifice local details. In addition, the application of those context-dependent schemes is highly dependent on the available hardware computing resources. In an embodiment, compared to process 100, the disclosed technology provides a global de-banding scheme that can be effectively embedded in the SDR to HDR conversion without changing the system structure.

[0029] Figure 2 An example of enhanced color banding artifacts 205 after luminance range expansion is shown. Extending the luminance range of SDR (typically from hundreds of nits to thousands of nits) through ITM can enhance step boundaries and cause color banding artifacts 210 (also known as ringing / contour artifacts), which degrades the quality of HDR displays.

[0030] Figure 3 A block diagram of an SDR to HDR conversion system including a de-banding process 330 according to an embodiment is shown. In one or more embodiments, the system includes a pixel brightness input 305, a percentile extraction process 310, an ITM process 340, and a pixel brightness output 306, the ITM process 340 including initial ITM curve generation 320, curve tuning 330 for de-banding (or de-banding process), ITM 140.

[0031] In an embodiment, the image statistics may be derived from SDR metadata. In an embodiment, the image statistics may be calculated (e.g., estimated) on the device. In an embodiment, the image statistics are represented by S. In one or more embodiments, the 50th percentile and the 90th percentile of brightness are used as practical examples, for example, S={P 50th , p 90th Other definitions / approximations of brightness statistics may also be used. To obtain the brightness percentile from percentile extraction process 310: The pixel brightness obtained as the maximum value of the R, G, B channels for a given pixel i is used as a practical example: x i =max(R i , G i , B i In one or more embodiments, other methods of pixel brightness calculation may be used. The pixel brightness of N pixels in the scene (e.g., ) are sorted in ascending order, and the kth percentile p can be obtained kth As an ordered list The nth pixel brightness value in,

[0032]

[0033] Note that the k-th pixel brightness value above is defined as the minimum value in the ordered list, which satisfies that no more than k percent of the data is less than it. In one or more embodiments, other definitions / approximations may be used.

[0034] In one or more embodiments, the initial curve generation process 320 generates coefficients through the ITM process 340. For example, the initial curve may include a Bezier curve. The 10th order Bezier curve shown is for illustration. Bezier curves of different orders may also be used. The tuned parameters are generated after the curve tuning process 330 for de-banding and Represents the ITM curve.

[0035] in, The tuned ITM representation of pixel brightness x is:

[0036]

[0037] in, is the binomial coefficient.

[0038] Figure 4 400 . In one or more embodiments, the input includes an input SDR image and statistical information 405 . The tuning parameters g iis designed as a continuous function of the input image statistics, which are expressed in terms of the 50th and 90th percentiles of brightness (e.g., g i (P 50th , P 90th By combining two sets of parameters that are respectively intended to flatten the lower and upper ends of the initial ITM curve and To generate the tuning parameter g i :

[0039]

[0040] In the embodiment, g 10 =1 to maintain the initial coefficient p 10 does not change and therefore maintains peak brightness.

[0041] In one or more embodiments, in block 410, and is set as follows: Based on p 50th Set and is fixed to 1. In block 411, and is set as follows: is fixed to 1 and based on p 90th set up In block 420, interpolation is used to obtain In block 421, interpolation is used to obtain In block 430, by fixing g 10 =1 and set To determine In block 440, use and To obtain the ITM parameters. In block 450, based on the tuned parameters To perform an ITM operation that provides an output HDR image 406.

[0042] Figure 5 An example scatter plot 500 for images with different brightnesses and a graph 505 for a linear interpolation function are shown according to an embodiment. In one or more embodiments, a tuning property for the lower end of the ITM curve is generated. The process includes the following steps. Set up two endpoints as follows and Fixed to and Based on p 50th Calculated from linear interpolation, where and are two brightness thresholds:

[0043]

[0044] Generate tuning parameters for the lower end of the ITM curve The process also includes the following steps. Perform nonlinear interpolation based on the index get Among them, f i is a function used for interpolation, which is designed to have the following properties:

[0045] Monotonically increasing function;

[0046] 0<f i ≤1;

[0047] When i deviates from 1, f i Approaching 1 quickly.

[0048] Figure 6 An example scatter plot 600 for images with different brightness and a graph 605 for a linear interpolation function are shown according to an embodiment. In one or more embodiments, tuning parameters for the higher end of the ITM curve are generated. The process consists of the following steps. Set up two endpoints and in, Fixed to and It is based on p 90th Calculated from linear interpolation, where and are two brightness thresholds:

[0049]

[0050] In an embodiment, the tuning parameters for the higher end of the ITM curve are generated The process also includes the following steps. Based on the index Perform nonlinear interpolation to obtain Among them, f i is a function used for interpolation, which is designed to have the following properties:

[0051] Monotonically decreasing function;

[0052] 0<f i ≤1;

[0053] When i decreases from 9, f i Approaching 1 quickly.

[0054] In an embodiment, the interpolation function f i The design and implementation of (α, β) includes the following steps:i is designed as an (inverse) sigmoid function as shown below:

[0055]

[0056] Where sign(α) determines monotonicity: increasing or decreasing; |α| determines the steepness of the function: the size of the range to be tuned; β represents the 0.5 midpoint. In one or more embodiments, f i It can be obtained from a look-up table (LUT).

[0057] To save and The size of the LUT is 18×2 W , where W is the bit width of the system. When setting α H =-α L When i (α L , 1) = f 10-i (α H , 9). In the embodiment, only The size of the LUT is reduced to 9×2 W .

[0058] Fig. 7A An example graph 700 for functions with different parameters according to an embodiment is shown. In one or more embodiments, the interpolation function f i The design and implementation of (α, β) involves computing and The f i For graph 700, f i (α L , β) is used to obtain in:

[0059] α L >0

[0060] β=1.

[0061] Figure 7B An example graph 705 for functions with different parameters is shown according to an embodiment. For graph 705, f i (α H ,β) is used to obtain in:

[0062] α H <0

[0063] β=9.

[0064] FIG. 8A to FIG. 8CITM curves 801, 811, and 821 are shown for comparing before and after tuning of associated example images 800, 810, and 820, according to an embodiment. Images 800, 810, and 820 represent the de-banding process 330 ( Figure 3 ) is embedded in the ITM process 340 ( Figure 3 ) is a use case for HDR to SDR conversion in .

[0065] The image statistics based de-banding process 330 is configured to flatten the banding prone portion of the ITM curve nicely. The HDR to SDR conversion pipeline with the de-banding process 330 generates and displays HDR content from SDR input with suppressed banding artifacts and mostly preserved mid-tone details.

[0066] For example, dark image 800 represents the de-banding process 330 ( Figure 3 ) is embedded in the ITM process 340 ( Figure 3 ) is a use case for HDR to SDR conversion in . For example, for a dark image 800, ITM curve 802 is before tuning, and ITM curve 803 is after tuning.

[0067] For example, bright image 810 represents the de-banding process 330 ( Figure 3 ) is embedded in the ITM process 340 ( Figure 3 ) is a use case for HDR to SDR conversion in FIG. 8 . For example, for a bright image 810, ITM curve 812 is before tuning and ITM curve 813 is after tuning. For example, the higher end of the ITM curve is flattened.

[0068] For example, mid-tone image 820 represents the de-banding process 330 ( Figure 3 ) is embedded in the ITM process 340 ( Figure 3 ) in HDR to SDR conversion. For example, keeping the ITM curve.

[0069] Fig. 9 A process 900 for balancing the effect of de-banding and preserving local details for a display according to an embodiment is shown. In block 910, the process 900 employs a de-banding process based on image statistics in a dynamic range conversion system (e.g., Figure 3In block 920, the process 900 performs the de-banding process in post-processing during determination of one or more initial ITM explicit curve coefficients by a computing device (e.g., a computing processor / multiprocessor, etc.). For example, the one or more initial ITM explicit curve coefficients may include polynomial curve coefficients. For example, the one or more initial ITM explicit curve coefficients may include Bezier curve coefficients. In block 930, the process 900 utilizes one or more parameters of a weighting function of the one or more initial ITM explicit curve coefficients as one or more control nodes for balancing the de-banding effect and preserving local details.

[0070] In an embodiment, process 900 includes the following features: the image statistics include brightness statistics.

[0071] In one or more embodiments, process 900 further provides that the curve coefficients are Bezier curve coefficients.

[0072] In one or more embodiments, process 900 also provides for the de-banding process to be embedded into an SDR to HDR conversion platform without major system architecture modifications.

[0073] In an embodiment, process 900 additionally provides for determining a luminance range susceptible to one or more color banding artifacts.

[0074] In one or more embodiments, process 900 also provides for globally processing all pixels based on brightness statistics.

[0075] In an embodiment, process 900 further includes: the image statistics including information from SDR metadata.

[0076] In one or more embodiments, process 900 additionally includes the following features: the image statistics include information calculated by a computing device.

[0077] In an embodiment, the SDR content is delivered to a TV that supports the SDR to HDR extension. In one or more embodiments, statistical information of the image (e.g., brightness percentiles or histograms) can be obtained by any of the following: extracting from SDR metadata delivered with the SDR content; or calculating on the device to which the SDR content is delivered. The on-device SDR to HDR conversion process generates a Bezier ITM curve based on the image statistics (e.g., brightness percentiles). De-banding process 330 ( Figure 3) determines the illumination range to be tuned, generates tuning parameters based on image statistics and adjusts the initial ITM curve. In an embodiment, the H / W processor of the TV applies the tuned ITM curve to the input SDR signal to generate an HDR output. In one or more embodiments, the H / W processor of the TV converts the color space from Rec.709 to DCI-P3 or BT2020 color space supported by current or future HDR TVs.

[0078] Embodiments have been described with reference to flowchart illustrations and / or block diagrams of methods, devices (systems) and computer program products. Each frame or combination of such illustrations / illustrations can be implemented by computer program instructions. The computer program instructions produce a machine when provided to a processor so that instructions executed via the processor create a method for implementing the functions / operations specified in the flowchart and / or block diagram. Each frame in the flowchart / block diagram can represent a hardware module or logic and / or a software module or logic. In an optional embodiment, the functions mentioned in the frame can occur in a non-sequential manner, simultaneously, etc., not in the order mentioned in the figure.

[0079] The terms "computer program medium", "computer usable medium", "computer readable medium" and "computer program product" are generally used to refer to media such as main memory, secondary memory, removable storage drives, hard disks installed in hard drives, and signals. These computer program products are devices for providing software to computer systems. Computer readable media allow computer systems to read data, instructions, messages or message packets, and other computer readable information from computer readable media. Computer readable media may include, for example, non-volatile memory such as floppy disks, ROMs, flash memory, disk drive memory, CD-ROMs, and other permanent storage. For example, it is useful for transmitting information such as data and computer instructions between computer systems. Computer program instructions may be stored in a computer readable medium, which may instruct a computer, other programmable data processing device, or other device to function in a specific manner so that the instructions stored in the computer readable medium produce an article of manufacture including instructions for implementing the functions / actions specified in one or more blocks of a flowchart and / or block diagram.

[0080] As will be appreciated by those skilled in the art, the various aspects of the embodiment may be implemented as a system, method or computer program product. Therefore, the various aspects of the embodiment may take the form of a complete hardware embodiment, a complete software embodiment (including firmware, resident software, microcode, etc.) or a combination of software and hardware embodiments, which may generally be referred to herein as a "circuit", "module" or "system". In addition, the various aspects of the embodiment may take the form of a computer program product implemented in one or more computer-readable media, wherein the one or more computer-readable media have a computer-readable program code implemented thereon.

[0081] Any combination of one or more computer-readable media may be utilized. A computer-readable medium may be a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or apparatus, or any suitable combination of the foregoing. More specific examples (non-exhaustive list) of computer-readable storage media would include the following: an electrical connection with one or more cables, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that may include or store a program used by or in conjunction with an instruction execution system, device, or apparatus.

[0082] The computer program code for performing the operations of various aspects of one or more embodiments can be written in any combination of one or more programming languages ​​(including object-oriented programming languages ​​such as Java, Smalltalk, C++, etc. and conventional procedural programming languages ​​such as "C" programming language or similar programming languages). The program code can be executed entirely on the user's computer, partially on the user's computer, as an independent software package, partially on the user's computer and partially on a remote computer, or completely on a remote computer or server. In the latter case, the remote computer can be connected to the user's computer through any type of network (including a local area network (LAN) or a wide area network (WAN)), or the connection can be made to an external computer (e.g., through the Internet using an Internet service provider).

[0083] Aspects of one or more embodiments are described above with reference to flowchart illustrations and / or block diagrams of methods, devices (systems) and computer program products. It will be understood that each block of the flowchart illustration and / or block diagram and the combination of blocks in the flowchart illustration and / or block diagram can be implemented by computer program instructions. These computer program instructions can be provided to a special-purpose computer or other programmable data processing device to produce a machine, so that instructions executed by a processor of the computer or other programmable data processing device create a method for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0084] These computer program instructions may also be stored in a computer-readable medium, which may instruct a computer, other programmable data processing device, or other device to act in a specific manner so that the instructions stored in the computer-readable medium produce an article of manufacture including instructions for implementing the functions / actions specified in one or more blocks of the flowchart and / or block diagram.

[0085] The computer program instructions may also be loaded onto a computer, other programmable data processing device, or other device, so that a series of operational steps are performed on the computer, other programmable device, or other device to produce a computer-implemented process, so that the instructions executed on the computer or other programmable device provide a process for implementing the functions / actions specified in one or more boxes of the flowchart and / or block diagram.

[0086] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments.In this regard, each frame in the flow chart or block diagram can represent the module, segment or part of one or more executable instructions including the logical function of realization specification of instruction.In some optional implementations, the function mentioned in the frame may not occur in the order mentioned in the figure.For example, depending on the function involved, the two frames shown continuously can actually be performed substantially at the same time, or the frame can sometimes be performed in the opposite order.It will also be noted that the combination of the frames in each frame illustrated in the block diagram and / or flow chart and the block diagram and / or flow chart can be realized by the system based on special hardware that performs the specified function or action or performs the combination of special hardware and computer instruction.

[0087] Reference to an element in the singular form in the claims is not intended to mean "one and only one," but rather "one or more," unless explicitly stated as such. All structural and functional equivalents to the elements of the above-described exemplary embodiments that are currently known or later come to be known to one of ordinary skill in the art are intended to be covered by the claims. Unless an element is expressly recited using the phrase "means for" or "step for," no claim element herein is to be interpreted under the provisions of 35 U.S.C. Section 112, sixth paragraph.

[0088] The terms used herein are only used for the purpose of describing specific embodiments and are not intended to limit the present invention. As used herein, the singular forms "a", "an" and "said" are intended to also include plural forms, unless the context clearly indicates otherwise. It will be further understood that when used in this specification, the terms "include" and / or "comprise" specify the presence of stated features, integers, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or groups thereof.

[0089] The corresponding structures, materials, actions, and equivalents of all method or step-plus-function elements in the claims are intended to include any structure, material, or action for performing a function in conjunction with other claimed elements specifically claimed. The description of the embodiments has been presented for purposes of illustration and description, but is not intended to be exhaustive or limited to the embodiments in the disclosed form. Many modifications and variations will be apparent to those of ordinary skill in the art without departing from the scope and spirit of the invention.

[0090] Although embodiments have been described with reference to specific versions thereof; however, other versions are possible. Therefore, the spirit and scope of the appended claims should not be limited to the description of the preferred versions contained herein.

[0091] According to an embodiment of the present disclosure, a device may be inferred to be a device.

[0092] According to an embodiment of the present disclosure, a method performed by an electronic device may include employing a de-banding process based on image statistics in a dynamic range conversion system.

[0093] According to an embodiment of the present disclosure, a method performed by an electronic device may include: including a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process.

[0094] According to an embodiment of the present disclosure, a method performed by an electronic device may include: including a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process and an SDR to HDR inverse tone mapping (ITM) process.

[0095] According to an embodiment of the present disclosure, a method performed by an electronic device may include: performing a de-banding process in a post-processing during determination of one or more initial ITM explicit polynomial curve coefficients by a computing device.

[0096] According to an embodiment of the present disclosure, a method executed by an electronic device may include: performing, by a computing device, a de-banding process in post-processing during determination of one or more initial ITM explicit curve coefficients.

[0097] According to an embodiment of the present disclosure, a method executed by an electronic device may include: utilizing one or more parameters of a weighting function of one or more initial ITM explicit curve coefficients as one or more control nodes for balancing debanding effects and preserving local details.

[0098] According to an embodiment of the present disclosure, a method executed by an electronic device may include: utilizing one or more parameters of a weighting function of one or more initial ITM explicit curve coefficients as one or more control nodes for balancing a debanding effect.

[0099] According to an embodiment of the present disclosure, the method executed by the electronic device may include: utilizing one or more parameters of a weighting function of one or more initial ITM explicit curve coefficients as one or more control nodes for retaining local details.

[0100] According to an embodiment of the present disclosure, the image statistical information includes brightness statistical information.

[0101] According to an embodiment of the present disclosure, the polynomial curve coefficients are Bezier curve coefficients.

[0102] According to an embodiment of the present disclosure, the de-banding process is embedded into the SDR to HDR conversion platform without major system structure modifications.

[0103] According to an embodiment of the present disclosure, a method performed by an electronic device may include determining a brightness range susceptible to one or more color banding artifacts.

[0104] According to an embodiment of the present disclosure, a method performed by an electronic device may include: globally processing all pixels based on brightness statistical information.

[0105] According to an embodiment of the present disclosure, the image statistics include information from SDR metadata.

[0106] According to an embodiment of the present disclosure, the image statistical information includes information calculated by a computing device.

[0107] According to an embodiment of the present disclosure, the image statistical information includes information calculated by a computing device.

[0108] According to an embodiment of the present disclosure, a processor-readable medium is provided. When the processor-readable medium is executed, the at least one processor executes a method corresponding to the method.

[0109] According to an embodiment of the present disclosure, at least one processor is configured to perform a balanced de-banding effect and preserve local details for a display.

[0110] According to an embodiment of the present disclosure, at least one processor is configured to perform a balanced de-banding effect for a display.

[0111] According to an embodiment of the present disclosure, at least one processor is configured to: perform preservation of local details for a display.

[0112] According to an embodiment of the present disclosure, at least one processor is configured to: employ a de-banding process based on image statistics in a dynamic range conversion system.

[0113] According to an embodiment of the present disclosure, at least one processor is configured to include: a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or an SDR to HDR inverse tone mapping (ITM) process.

[0114] According to an embodiment of the present disclosure, at least one processor is configured to include: a High Dynamic Range (HDR) to Standard Dynamic Range (SDR) Tone Mapping (TM) process.

[0115] According to an embodiment of the present disclosure, at least one processor is configured to include: an SDR to HDR inverse tone mapping (ITM) process.

[0116] According to an embodiment of the present disclosure, at least one processor is configured to perform a de-banding process in post-processing during determination of one or more initial ITM explicit polynomial curve coefficients.

[0117] According to an embodiment of the present disclosure, at least one processor is configured to utilize one or more parameters of a weighting function of one or more initial ITM explicit curve coefficients as one or more control nodes for balancing debanding effects and preserving local details.

[0118] According to an embodiment of the present disclosure, at least one processor is configured to utilize one or more parameters of a weighting function of one or more initial ITM explicit curve coefficients as one or more control nodes for balancing debanding effects.

[0119] According to an embodiment of the present disclosure, at least one processor is configured to: utilize one or more parameters of a weighting function of one or more initial ITM explicit curve coefficients as one or more control nodes for preserving local details.

[0120] According to an embodiment of the present disclosure, at least one processor is configured to determine a luminance range susceptible to one or more color banding artifacts.

[0121] According to an embodiment of the present disclosure, at least one processor is configured to globally process all pixels based on brightness statistics.

[0122] According to an embodiment of the present disclosure, the image statistical information includes at least: information from SDR metadata or information calculated by a computing device.

Claims

1. A computer-implemented method comprising: A de-banding process based on image statistics is employed in a dynamic range conversion system, wherein the dynamic range conversion system includes a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or an SDR to HDR inverse tone mapping (ITM) process; performing said de-banding process in post-processing during determination of one or more initial ITM explicit curve coefficients by a computing device; as well as One or more parameters of the weighting function of the one or more initial ITM explicit curve coefficients are utilized as one or more control nodes for balancing the debanding effect and preserving local details.

2. The method according to claim 1, wherein: The image statistics include brightness statistics.

3. The method according to any one of claims 1 and 2, wherein: The curve coefficients are Bezier curve coefficients.

4. The method according to any one of claims 1 to 3, wherein: The de-banding process is embedded into the SDR to HDR conversion platform without major system architecture modifications.

5. The method according to any one of claims 1 to 4, further comprising: Determines the luminance range that is susceptible to one or more color banding artifacts.

6. The method according to any one of claims 2 to 5, further comprising: All pixels are processed globally based on the brightness statistics.

7. The method according to any one of claims 1 to 6, wherein: The image statistics include information from the SDR metadata.

8. The method according to any one of claims 1 to 7, wherein: The image statistics include information calculated by the calculation device.

9. A processor-readable medium, which when executed causes the at least one processor to perform the method according to any one of claims 1 to 8.

10. A device comprising: Memory, which stores instructions; as well as At least one processor executes the instructions, the instructions comprising a process, the process being configured to: A de-banding process based on image statistics is employed in a dynamic range conversion system, wherein the dynamic range conversion system includes a high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or an SDR to HDR inverse tone mapping (ITM) process; performing said de-banding process in post-processing during determination of one or more initial ITM explicit curve coefficients; as well as One or more parameters of the weighting function of the one or more initial ITM explicit curve coefficients are utilized as one or more control nodes for balancing the debanding effect and preserving local details.

11. The device according to claim 10, wherein: The image statistics include brightness statistics.

12. The device according to any one of claims 10 and 11, wherein The curve coefficients are Bezier curve coefficients.

13. The apparatus according to any one of claims 10 to 12, wherein: The de-banding process is embedded into the SDR to HDR conversion platform without major system architecture modifications.

14. Apparatus according to any one of claims 11 to 13, wherein: The process is also configured to: determining a luminance range susceptible to one or more color banding artifacts; and All pixels are processed globally based on the brightness statistics.

15. The device according to any one of claims 11 to 14, wherein: The process is also configured to: The image statistics information includes at least information from SDR metadata or information calculated by the computing device.

Images