51 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.

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.

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.

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.

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.

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 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.

Disclosed in the embodiments of the present application are an image processing method, an electronic device, a computer-readable storage medium and a computer program product. The method comprises: an electronic device displaying a high dynamic range (HDR) image on the basis of a first standard dynamic range (SDR) image and a first gain map, or displaying the first SDR image; in response to an image editing operation, performing editing processing on the first SDR image, so as to obtain a second SDR image, and obtaining a second gain map on the basis of dynamic range transformation information and the second SDR image; storing the second gain map and the second SDR image; and on the basis of the second gain map and the second SDR image, displaying an edited HDR image. The dynamic range transformation information is obtained on the basis of the first SDR image and the first gain map, and is used for describing the transformation relationship from an SDR image to an HDR image; and the second gain map is a gain map comprising editing content corresponding to the image editing operation. By means of the embodiments of the present application, an HDR effect can still be presented after image editing.

The application discloses a video quality determination method and device, equipment and a readable storage medium. The application migrates an HDR domain to an SDR domain, combines training optimization, uses a model obtained by training an SDR video as a backbone network, combines a domain migration module to construct a model capable of performing quality evaluation on an HDR video, can reduce the complexity of model development and maintenance, can fully utilize pre-training knowledge of a large-scale standard dynamic range dataset, and reduces the dependence on high dynamic range data.

The invention provides a display method, a display device and electronic equipment. The method comprises the steps that a first image and a second image are determined according to an image to be processed, the first image is a standard dynamic range (SDR) image, and the second image is a gain image; n third images are determined according to the first image, the N third images correspond to the N window viewfinders, the filter rendering effects of the N third images are different, and N is a positive integer larger than or equal to 1; determining N fourth images according to the N third images and the second image, wherein the fourth images are high dynamic range (HDR) images; and respectively displaying the N fourth images in N window viewfinders of the electronic equipment. According to the display method, the display device and the electronic equipment, the HDR image rendered by the filter can be displayed in the multi-window viewfinder, and meanwhile, the memory and the power consumption required for processing the image data are saved.

Embodiments of the present application relate to the technical field of image processing, and provide an image processing method and an electronic device. The method comprises: acquiring a first image and a second image, wherein 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 on the basis of the first image and the second image; determining metadata of first gain information on the basis of the first gain range, wherein the first gain information is calculated on the basis of the first image and the second image; and obtaining an available image on the basis of the first gain information, the metadata, and the second image. In this way, by adjusting gain ranges, the quality loss of reconstructed HDR images can be reduced, thereby improving the image quality of images displayed in an electronic device.

The invention particularly relates to a semantic knowledge migration-based high dynamic range imaging method, which comprises the following steps of: acquiring a low dynamic range image, and generating an initial high dynamic range image by utilizing an initial high dynamic range reconstruction model; converting the initial high dynamic range image into a reconstructed image of a standard dynamic range domain through domain migration operation; processing the reconstructed image of the standard dynamic range domain by adopting a semantic segmentation network SAM to obtain semantic priori; processing the reconstructed image of the standard dynamic range domain by combining semantic prior with a semantic prior guidance reconstruction model to obtain a refined reconstructed image; based on a knowledge distillation method, cross-domain semantic priori migration is realized at three levels of content, color and features, and an initial high dynamic range reconstruction model is optimized through a combined loss function; in the reasoning stage, only the optimized initial high dynamic range reconstruction model is adopted to output a final high dynamic range image. According to the method, high-dynamic-range image reconstruction is carried out by effectively utilizing the advanced capability of semantic priori.

This application discloses an image processing method, an electronic device, a computer-readable storage medium, and a computer program product. In this method, the electronic device displays an HDR image or displays a first SDR image based on a first SDR image and a first gain map; in response to an image editing operation, the first SDR image is edited to obtain a second SDR image, and a second gain map is obtained based on dynamic range transformation information and the second SDR image; the second gain map and the second SDR image are stored; and the edited HDR image is displayed based on the second gain map and the second SDR image. The dynamic range transformation information is obtained based on the first SDR image and the first gain map, and is used to describe the transformation relationship from a standard dynamic range image to a high dynamic range image; the second gain map is a gain map that includes the edited content corresponding to the image editing operation. This application embodiment can still present an HDR effect after image editing.

The embodiment of the invention provides an image processing method and electronic equipment, and relates to the technical field of image processing. The method includes 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. And determining a first gain range according to the first image and the second image. Metadata of first gain information is determined according to 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 first gain information, the metadata 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.

The embodiment of the invention discloses an image processing method, electronic equipment, a storage medium and a chip system.The method comprises the steps that the electronic equipment responds to a received shooting instruction, a camera can be called, i sets of different exposure parameters are adopted to continuously shoot a target scene, and i frames of images of the target scene with different exposure degrees are obtained; then, in combination with distortion correction parameters of the camera, obtaining a standard dynamic range image and a brightness gain image which are subjected to distortion correction processing; processing the standard dynamic range image based on the brightness gain image to obtain an image with a brightness enhancement effect; and finally, the image with the brightness enhancement effect can be displayed. By adopting the method and the device, the standard dynamic range image and the brightness gain image after distortion correction processing can be obtained in combination with the distortion correction parameters of the camera, the influence caused by imaging distortion of the camera is reduced, the display effect of the image is improved, and the image quality is improved.

This invention discloses a real-time downconversion method for high dynamic range to standard dynamic range, comprising the following steps: S10, inputting an HDR video image into a static 3D lookup table (3DLUT) downconversion algorithm template, and outputting a first standard dynamic range (SDR) signal; S20, inputting the first SDR signal into an SDR image detection module to determine whether there is overexposure abnormality in the image after 3DLUT downconversion: if there is no overexposure abnormality, directly outputting the first SDR signal; if there is overexposure abnormality, correcting the 3DLUT mapping curve through a 3DLUT mapping curve adjustment module to complete the static 3DLUT parameter update; then, based on the updated static 3DLUT, regenerating the SDR signal through the static 3DLUT downconversion algorithm template, repeating the above detection and static 3DLUT parameter update process until the output SDR signal image has no overexposure abnormality.