84 results about "Standard dynamic range" patented technology

The embodiment of the invention provides an image loss determination method and a related device. The method comprises the following steps: generating a standard dynamic range (SDR) image according to an original high dynamic range (HDR) image; generating a reconstructed HDR image according to the original HDR image and the SDR image; and determining image loss of a plurality of areas in the reconstructed HDR image according to the original HDR image and the reconstructed HDR image. By adopting the embodiment of the invention, the reconstruction loss of the HDR image can be obtained, so that the visual fault in the reconstructed HDR image can be identified.

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

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

The invention relates to an HDR10 image layered coding and decoding method and device and a storage medium, and the method comprises the steps: receiving a YUV420 video data frame, carrying out the dynamic range segmentation of a pixel of each frame data, and dividing each pixel into a standard dynamic range part SDR and a high dynamic range part HDR; performing nonlinear quantization calculation on the pixel value brightness of the standard dynamic range part SDR and the pixel value brightness of the high dynamic range part HDR to obtain a brightness component # imgabs0 # of the base layer and a brightness component # imgabs1 # of the enhancement layer; based on the standard dynamic range part SDR and the high dynamic range part HDR, performing nonlinear quantization calculation on the chromaticity of each pixel value to obtain a chromaticity residual value # imgabs2 # and a chromaticity residual quantization value # imgabs3 #; and carrying out hierarchical coding and metadata encapsulation on pixels of the frame data to obtain an HDR10 code stream, and transmitting the HDR10 code stream. According to the invention, through a dynamic range segmentation algorithm, double-segment nonlinear quantization, hierarchical coding and dynamic metadata synchronization, high-efficiency coding transmission compatible with an HDR10 standard is realized.

An electronic device may be provided with a display. The display may be configured to display standard dynamic range image content and high dynamic range image content at the same time. The standard dynamic range image content may include one or more regions of locally boosted contrast in regions adjacent to high dynamic range image highlights. This prevents the appearance of grayish whites in standard dynamic range image content while allowing the high dynamic range highlights to take full advantage of the dynamic range of the display. The size and shape of the regions of locally increased contrast may be based on the size and shape of the high dynamic range highlights, the size of the display, the distance between the user and the display, and / or the percentage of the display that is dedicated to high dynamic range image content.

The present disclosure relates to systems and methods for transmitting standard dynamic range (SDR) content. The system and method may use a modified electro-optic transfer function (EOTF) curve to convert a non-linear color value of the SDR content to an optical output value of the modified SDR content. The system and method may encode the modified SDR content using 8 bits while preventing banding. The system and method may transmit the encoded data to a client device for presentation on a display.

The application relates to the technical field of digital film content production, distribution and screening, and discloses a high dynamic range content distribution display method and a video processing device. A standard dynamic range master is used as the only main asset, physical baseline information is generated, candidate residual information is extracted, semantic gating decision is performed, auxiliary data containing the physical baseline information and selectively containing conditional gain information is output, and a high dynamic range signal is reconstructed according to the corresponding mode selected according to the auxiliary data, so that the single master is adapted to different display capability screening terminals, and the problems of high cost and poor consistency of the existing multi-version distribution mode are solved. Meanwhile, the semantic gating mechanism is used to eliminate the AI illusion risk, the adaptive auxiliary data structure is used to reduce the transmission bandwidth, and the distribution efficiency, screening safety and content verifiability are considered.

The embodiments of the present application provide an image loss determination method and a related apparatus. The method comprises: generating a standard dynamic range (SDR) image on the basis of an original high dynamic range (HDR) image; generating a reconstructed HDR image on the basis of the original HDR image and the SDR image; and determining image losses of a plurality of regions in the reconstructed HDR image on the basis of the original HDR image and the reconstructed HDR image. Using the embodiments of the present application can obtain reconstruction losses of HDR images, thereby identifying visual contours in reconstructed HDR images.

This application discloses an image conversion method, device, electronic device, and computer-readable storage medium. The method includes: obtaining a standard dynamic range image and determining the RGB color values ​​of the standard dynamic range image; using a correction coefficient prediction model to predict the target correction coefficient corresponding to the standard dynamic range image; looking up the RGB color values ​​and the normalized RGB color values ​​corresponding to the target correction coefficient in a four-dimensional lookup table; and using the normalized RGB color values ​​to generate a high dynamic range image corresponding to the standard dynamic range image. The technical solution provided by this application can achieve faster and more efficient conversion of SDR data to HDR data while effectively ensuring image quality.

Methods and systems for dynamic range conversion and display mapping of standard dynamic range (SDR) images onto high dynamic range (HDR) displays are described. Given an SDR input image, a processor generates an intensity (luminance) image and optionally a base layer image and a detail layer image. A first neural network uses the intensity image to predict statistics of the SDR image in a higher dynamic range. These predicted statistics together with the original image statistics of the input image are used to derive an optimal tone-mapping curve to map the input SDR image onto an HDR display. Optionally, a second neural network, using the intensity image and the detail layer image, can generate a residual detail layer image in a higher dynamic range to enhance the tone-mapping of the base layer image into the higher dynamic range.

In a method to improve backwards compatibility when decoding high-dynamic range images coded in a wide color gamut (WCG) space which may not be compatible with legacy color spaces, hue and / or saturation values of images in an image database are computed for both a legacy color space (say, YCbCr-gamma) and a preferred WCG color space (say, IPT-PQ). Based on a cost function, a reshaped color space is computed so that the distance between the hue values in the legacy color space and rotated hue values in the preferred color space is minimized. HDR images are coded in the reshaped color space. Legacy devices can still decode standard dynamic range images assuming they are coded in the legacy color space, while updated devices can use color reshaping information to decode HDR images in the preferred color space at full dynamic range.

The present application relates to the technical field of image processing. Provided in the embodiments are an image processing method and an electronic device. The method comprises: acquiring a first image and a second image, the first image being a high dynamic range (HDR) image, and the second image being a standard dynamic range (SDR) image; on the basis of the first image and the second image, determining a first gain range; on the basis of first gain information and the first gain range, determining second gain information, the first gain information being calculated on the basis of the first image and the second image; and, on the basis of the second gain information and the second image, obtaining a selectable image. In this way, adjusting gain ranges can reduce the quality loss of reconstructed HDR images, thus improving the image quality of images displayed by electronic devices.

To provide a method, an apparatus, a computer program, and a computer program-based device for deriving and signaling a chroma QP (QPc) for high dynamic range (HDR) content.SOLUTION: Quantization parameter signaling mechanisms for both standard dynamic range (SDR) and HDR content in video coding are described using two approaches. The first approach is to send the user-defined Qpc table directly in the high-level syntax. This leads to more flexible and efficient QP control for future codec development and video content coding. A second approach is to signal the luma and chroma QPs independently. This eliminates the need for a Qpc table and eliminates the dependency of the chroma quantization parameter on the luma QP.SELECTED DRAWING: Figure 5A

The invention discloses a video quality determination method, device and equipment and a readable storage medium, and the method comprises the steps: migrating an HDR domain to an SDR domain, combining training optimization, taking a model obtained through SDR video training as a backbone network, and combining a domain migration module to construct a model capable of carrying out the quality evaluation of an HDR video, thereby achieving the quality evaluation of the HDR video. The complexity of model development and maintenance can be reduced, pre-training knowledge of a large-scale standard dynamic range data set can be fully utilized, and dependence on high dynamic range data is reduced.

A method for estimating tone mapping parameters is disclosed. A first tone mapping parameter representative of a white level offset is obtained (S500) for a standard dynamic range current picture. Then, the obtained first tone mapping parameter is compared (S502) with a corresponding first tone mapping parameter obtained for a previous picture. Finally, second tone mapping parameters are updated (S504, S506) for the standard dynamic range current picture responsive to the comparing, wherein the second tone mapping parameters comprise pairs of values representative of a tone mapping output fine tuning function.

The invention discloses an image high dynamic range reconstruction method and system based on a detail coding gain graph, and belongs to the technical field of computer vision and image processing. The method comprises the following steps: S1, data preprocessing: acquiring an input single standard dynamic range image, and preprocessing the image to obtain image data in a linear space or normalized floating point tensor format; s2, proposing a detail recovery network design based on detail generation of a diffusion model; s3, predicting a detail coding gain graph, and providing a gain convolutional neural network design; and S4, final HDR synthesis: carrying out pixel-by-pixel multiplication on the processed standard dynamic range (SDR) image and the three-channel (R, G, B) gain image according to channels to obtain a reconstructed HDR image. According to the method, the problems of detail recovery missing, image structure distortion, low calculation efficiency and the like in the existing single image HDR (High Dynamic Range) reconstruction technology are effectively solved.

One embodiment provides a computer-implemented method that includes employing a de-banding process based on image statistics in a dynamic range conversion system, including high dynamic range (HDR) to standard dynamic range (SDR) tone mapping (TM) process or SDR-to-HDR inverse tone mapping (ITM) process. A computing device performs the de-banding process in post-processing during a determination of one or more initial ITM explicit polynomial curve coefficients. One or more parameters of a weighing function of the one or more initial ITM explicit curve coefficients are utilized as one or more controlling knots for balancing a de-banding effect and preserving local detail.

A method for estimating tone mapping parameters is disclosed. A first tone mapping parameter representative of a white level offset is obtained (S500) for a standard dynamic range current picture. The obtained first tone mapping parameter is then compared (S502) with a corresponding first tone mapping parameter obtained for a previous picture. Finally, in response to the comparison, a second tone mapping parameter is updated (S504, S506) for the standard dynamic range current picture, where the second tone mapping parameter comprises a value pair representative of a tone mapping output trim function.

Embodiments of this application provide a method for determining an image loss and a related apparatus. The method includes: generating a standard dynamic range SDR image based on an original high dynamic range HDR image; generating a reconstructed HDR image based on the original HDR image and the SDR image; and determining image losses of a plurality of areas in the reconstructed HDR image based on the original HDR image and the reconstructed HDR image. In embodiments of this application, a reconstruction loss of the HDR image can be obtained, thereby identifying a visible contour in the reconstructed HDR image.

Various techniques for utilizing gain mapping are disclosed. According to some embodiments, a technique for utilizing gain mapping includes: (1) accessing an enhanced image including a high dynamic range (HDR) image and the gain mapping; (2) extracting the HDR image and the gain mapping from the enhanced image; (3) generating a standard dynamic range (SDR) image using the HDR image and the gain map; (4) receiving a first modification instruction and applying the first modification instruction to the HDR image; (5) generating a second modification instruction at least based on the first modification instruction; (6) applying the second modification instruction to the SDR image; (7) generating a second gain map by comparing the HDR image with the SDR image or vice versa; and (8) embedding the second gain map into the HDR image or the SDR image.

A method comprising: generating (111) a standard dynamic range video from a high dynamic range video; generating (112) energy-aware information by analyzing a distribution of tones of a first high dynamic range video; generating (113) first metadata allowing transforming the standard dynamic range video into a second high dynamic range video and second metadata representing the energy-aware information, the energy aware information allowing controlling an energy consumed for displaying a third high dynamic range video obtained from a reconstructed version of the second high dynamic range video, the second metadata comprising at least one set comprising an energy reduction rate and a peak luminance value; and encoding the standard dynamic range video and the first and second metadata in video data.

In an encoder, a high-dynamic range (HDR) image is encoded using a family of local forward reshaping functions selected according to an array of forward mapping indices (FMI) indicating which local forward reshaping function needs to be used for each pixel in the HDR image to generate a reshaped standard dynamic range (SDR) image. A decoder, given the reshaped SDR image, iteratively generates a reconstructed HDR image and estimated reshaped SDR images by adjusting a local FMI array and a local array of backward mapping indices (BMI) until an error metric related to the difference between the local BMI and FMI arrays and the difference between the estimate SDR images and the reshaped SDR image satisfy a convergence criterion. Techniques for generating families of local forward reshaping functions and local backward reshaping functions based on a global forward reshaping function are also presented.

The present disclosure relates to systems and methods for transmitting standard dynamic range (SDR) content. The system and method may use a modified electro-optic transfer function (EOTF) curve to convert a non-linear color value of the SDR content to an optical output value of the modified SDR content. The system and method may encode the modified SDR content using 8 bits while preventing banding. The system and method may transmit the encoded data to a client device for presentation on a display.

Embodiments of the invention relate to applying image overlay on HDR images. A computing system for applying image overlay on a high dynamic range (HDR) image is provided. The system receives an HDR image, generates a first gain map and a standard dynamic range (SDR) image based on the received HDR image, renders at least one overlay image to generate an SDR effect image buffer and an effect gain map, overlays the effect gain map and the first gain map to generate a second gain map, and outputs the second gain map to the HDR image buffer. The SDR image and the SDR effect image buffer are superimposed to generate an edited SDR image, an edited HDR image is generated based on the edited SDR image and the second gain map, and an output is generated based on the edited HDR image.

Various techniques for generating a gain map are disclosed. According to some embodiments, one technique for generating a gain map includes: (1) accessing a high dynamic range (HDR) image; (2) accessing a standard dynamic range (SDR) image; (3) for each pixel shared between the HDR image and the SDR image, (4) plotting the plurality of pixels on a graph, where the HDR value of the pixel is plotted on the Y-axis of the graph and the SDR value of the pixel is plotted on the X-axis of the graph; (5) establishing a first curve representing an approximation of the plotted pixels; (6) inverting the first curve to establish a second curve; (7) applying the second curve to the plotted pixels to establish replotted pixels; and generating a gain map based on the replotted pixels; and (8) embedding the gain map into the HDR image.

The embodiment of the invention provides a video data processing method and device and a medium. The method comprises the following steps: acquiring metadata of video frames in a standard dynamic range video; obtaining display parameters of the display equipment; determining a mapping curve corresponding to the video frame according to the display parameters and the metadata; the mapping curve is used for representing a mapping relation between a source color intensity value and a target color intensity value in an electric signal space; wherein the expansion upper limit value of the target color intensity value in the mapping curve is determined according to the display parameters and the metadata. The embodiment of the invention can effectively improve the display effect of the video frame.

The embodiment of the invention provides an image processing method, electronic equipment, a storage medium, a chip system and a program product, and relates to the technical field of terminals. The method comprises the steps that a first image and a second image are acquired, the first image is a high dynamic range (HDR) image, and the second image is a standard dynamic range (SDR) image; determining a first gain graph according to the first image and the second image; adjusting the brightness of the second image to obtain a third image; a second gain graph is obtained based on a brightness adjustment gain and the first gain graph, the brightness adjustment gain is obtained through calculation based on the third image and the second image, and the brightness adjustment gain is used for representing the brightness gain of the third image relative to the second image; and obtaining a fourth image based on the second gain graph and the third image, the fourth image being an HDR image. In this way, the quality of the HDR image displayed by the electronic equipment can be improved, and the user experience is good.

Methods and apparatus are provided for color space inference in high dynamic range video, such as in the SL-HDR1 video standard. In one embodiment, an encoder sends information including standard dynamic range video and metadata contained in a supplemental enhancement information message to indicate the color space included in the video. In another embodiment, a decoder parses the bitstream and infers values ​​from the data in the supplemental enhancement information message to inform the decoder of the color space included in the video. The high dynamic range signal is reconstructed based on the standard dynamic range data and the values ​​inferred from the metadata.

The present application discloses an image encoding method applicable to the field of data processing technology. The image encoding method comprises the steps of: encoding a target image into a bitstream; and encoding a first identifier into the bitstream, wherein the first identifier represents an optical-electrical transfer function that matches the target image, and the target image includes a High Dynamic Range (HDR) image and / or a Standard Dynamic Range (SDR) image. That is, when the target image is encoded in the present application, the first identifier representing an optical-electrical transfer function that matches the target image may also be encoded into the bitstream to satisfy the display requirements of both SDR and HDR images at the decoder side, and as a result, after obtaining the first identifier through decoding, the decoder may render and display an image reconstructed according to the corresponding optical-electrical transfer function.

The embodiment of the invention provides an image processing method and electronic equipment, and relates to the technical field of image processing. The method comprises the steps that a first image and a second image are acquired, the first image is a high dynamic range (HDR) image, and the second image is a standard dynamic range (SDR) image; determining a first gain range according to the first image and the second image; second gain information is determined according to the first gain information and the first gain range, and the first gain information is calculated according to the first image and the second image; and obtaining a selectable image according to the second gain information and the second image. Therefore, by adjusting the gain range, the quality loss of the reconstructed HDR image can be reduced, and the image quality of the image displayed by the electronic equipment can be improved.