3043 results about "Chrominance" patented technology

The invention relates to a display screen backlight brightness adjusting method and system based on a Mini QLED technology. The method comprises the following steps: dividing a display image signal into a brightness signal, a chrominance signal and a saturation signal, and generating image feature data; performing sub-pixel-level boundary detection to obtain a plurality of initial backlight sub-regions, and calculating region brightness distribution data; executing region clustering operation and region merging to obtain a plurality of target backlight sub-regions and calculating backlight partition mapping data; carrying out nonlinear feature transformation, and calculating backlight unit control data of the Mini LED backlight unit; outputting the backlight compensation amount of each target backlight sub-region by adopting a deep Q network; and performing real-time feedback correction, calculating a deviation value between an actual display parameter and a target parameter of each target backlight sub-region, and outputting a backlight optimization control signal. According to the invention, the backlight brightness is accurately adjusted, and the consistency of the display effect is improved.

A method of filtering an image is disclosed, the method comprising: receiving filter coefficients and first component sample values corresponding to samples surrounding a reference sample, and inputting said filter coefficients and first component sample values into a cross component filter to produce a cross component filter output; wherein said cross-component filter uses a restricted number of bits to represent said filter coefficients and / or first component sample values to produce said filter output.

The invention relates to the technical field of projection display, and discloses a projection curtain light field display gain method and system used under ambient light. According to the method, environment light data, projection curtain data and original output signals of projection equipment are collected in real time, and a dynamic light field distribution model is established after fusion processing. And based on the dynamic light field distribution model, adopting an adaptive genetic algorithm to optimize a compensation weight, generating a light field compensation parameter set, performing reverse compensation processing of brightness gain, contrast and chromaticity offset on an original output signal, and generating an enhanced projection signal. The system comprises a multi-source data acquisition module, a light field feature extraction module, a dynamic compensation calculation module, a signal enhancement processing module and a closed-loop feedback control module, ensures that the projection image keeps an optimal display effect under different ambient light conditions, and remarkably improves the watching experience of audiences.

A method for video decoding is provided. The method includes obtaining, from a video bitstream, a coding unit in a current picture, wherein the coding unit comprises a luma block and at least one chroma block; and in response to a determination that reconstructed luma samples in the luma block are not to be down-sampled: determining one or more cross-component prediction models based on a luma filter, wherein the one or more cross-component prediction models comprise a convolutional cross-component model (CCCM); obtaining, based on the luma filter, at least one reconstructed luma sample in the luma block that corresponds to a chroma sample in the at least one chroma block; and applying at least one of the one or more cross-component prediction models to the at least one reconstructed luma sample to predict the chroma sample.

The invention belongs to the technical field of video processing, and particularly relates to a monitoring video enhancement method for a farm, which aims to solve the technical problem of low quality of an enhanced video in the prior art, and comprises the following steps: S1, processing each frame of image in a monitoring video sequence frame by frame; s2, distinguishing a target animal area from a background area, and identifying and generating an artifact mask; s3, aiming at the background area, carrying out key smoothing processing on the artifact position to inhibit the artifact; s4, for the image of the target animal area, performing adaptive nonlinear enhancement on the brightness component, and performing color correction on the chrominance component; s5, performing pixel-level fusion on the enhanced target animal area and the background area; and S6, spreading the information of the previous frame to the current frame by using the forward optical flow field, and carrying out weighted fusion on the information of the previous frame and the current frame. According to the method, the target bred animals, the background areas and the artifacts are accurately distinguished, so that refined and differentiated processing of pictures is realized.

A system configured to generate dynamic visual feedback by synchronizing smart lights with a rhythm and energy levels of music being output. A device may translate audio samples to luma (brightness), chroma (color), and location data using a low-latency algorithm. For example, the device may divide the full band audio data into separate frequency bands based on the number of output devices and control a brightness for an output device by tracking energy within a corresponding frequency band. The color and location may be controlled based on a number of beats per minute, direction, and / or the like. In addition to controlling external lighting via a smart home hub, the device can control LED light(s) on the device via an LED controller. To further reduce latency, the device can directly communicate between an audio processor, the smart home hub, and / or the LED controller using low level hardware abstraction layers (HALs).

Methods, apparatuses, and non-transitory computer-readable storage mediums are provided for video coding. In one method, a decoder obtains, for a current chroma block, a non-linear model (non-LM) mode and a linear model (LM) mode, and the LM mode includes a cross component linear model (CCLM) mode and a multi-model linear model (MMLM) mode. The decoder then combines the non-LM mode and the LM mode for a multi-hypothesis-based chroma prediction (MCP) for the current chroma block.

A video signal processing method comprises the steps of: configuring a template including neighboring blocks of a current block; down-sampling luminance component samples of the neighboring blocks on the basis of a color format of a current picture including the current block; deriving a first linear model and a second linear model on the basis of the down-sampled luminance component samples; and on the basis of any one linear model from among the first linear model and the second linear model, predicting a chrominance component sample at a location corresponding to a location of a first sample from among the luminance component samples of the current block, wherein the any one linear model is determined by comparing a value of the first sample with a threshold value.

The invention discloses a low-light image enhancement method based on a YUV color space, and relates to the technical field of image processing. According to the method, a color space illumination enhancement network (CSLNet is established, brightness (Y) and chrominance (U, V) information is separated, and brightness and chrominance channels are respectively subjected to targeted processing, so that the image brightness and details are improved, the problems of color distortion and noise amplification are avoided, the CSLNet makes full use of the advantages of a YUV color space, and the image quality is improved. Wherein the Y channel represents brightness information, the U and V channels represent chrominance information, brightness enhancement and color correction can be more accurately controlled through separation processing and the CSLNet, a color space enhancement module CSE Block (Color Space Enhancement Block) is introduced into the CSLNet, the CSE Block is fused with a U-shaped network structure and a multi-head self-attention mechanism, and optimization processing is specially carried out on chrominance channels U and V of a low-illumination image.

A video coding system is provided that performs intra prediction in a mode using a neural network for block of only a set of specific block sizes. The signaling of this mode is designed to be efficient in terms of rate-distortion under this constraint. Different transformations of the context of a block and the neural network prediction of this block are introduced in order to use one single neural network for predicting blocks of several sizes, as well as the corresponding signaling. The neural network-based prediction mode considers both luminance blocks and chrominance blocks. The video coding system comprises encoder and decoder apparatuses, encoding, decoding and signal generation methods and a signal carrying information corresponding to the described coding mode.

A method for video decoding is provided. The method includes obtaining, from a bitstream, a coding unit in a current picture, the coding unit including a luma block and a chroma block; obtaining a reconstructed luma sample in the luma block; determining one or more cross-component prediction models based upon a block size, the block size being a size of the luma block or a size of a reconstructed neighbouring block located on a top of or a left of the luma block; and applying at least one of the one or more cross-component prediction models to at least the reconstructed luma sample to predict a chroma sample in the chroma block.

The invention provides a cross-platform content compatibility method and system based on a virtual shooting LED display screen. The method comprises the following steps: processing an irrelevant data content stream of a content stream of a heterogeneous content source to generate an intermediate data stream; constructing a virtual logic display space according to the resolution parameter of the intermediate data stream and the curvature data of the physical screen database; performing dynamic resource allocation based on the control point grid of the virtual logic display space, and generating a rendering task queue; loading a three-dimensional lookup table to perform forward color gamut conversion according to the rendering task queue and a physical screen color configuration file, and adjusting HSL offset according to collected real-time chroma data to generate frame cache data; and determining a delay compensation value based on the frame buffer data and the PTP clock signal, and inserting a corresponding time offset in an output queue through the delay compensation value to generate a multi-screen output signal. According to the scheme, the rendering accuracy, the color consistency and the display stability in the virtual shooting scene can be remarkably improved.

A method and an apparatus are disclosed for video coding using an improved inloop filter for chroma components. In the disclosed embodiments, a video decoding device performs obtaining a reconstructed frame that includes luma samples and chroma samples, subsequently obtaining a scale value representing a resolution difference between the reconstructed frame and an original frame. Responsive to the reconstructed frame having a resolution that is based on the scale value and is less than a resolution of the original frame, the video decoding device generates an upsampled chroma frame by inputting the luma samples and the chroma samples into a cross component resampling inloop filter (CC-RIF).

The application provides a signal transmission method, a video encoder and a computer readable storage medium. A computer-implemented signal transmission method performed by an encoder comprises the following steps: a processor transmits a bitstream comprising weight information for a prediction coding unit (CU) to a video decoder, the weight information indicating that if weighted prediction is enabled for a bi-prediction mode of the CU, weighted averaging for the bi-prediction mode is disabled, and the weight information indicating that if weighted prediction is enabled for at least one of a luma component and a chroma component of a reference picture of the CU, weighted averaging for the bi-prediction mode is disabled, wherein the bitstream comprises a flag indicating whether weighted prediction is enabled for at least one of the luma component and the chroma component of the reference picture, and the flag comprises a flag luma_weight_lx_flag[i] transmitted for an i-th reference picture in a reference picture list Lx, wherein x is 0 or 1.

The invention relates to the technical field of audio and video coding, decoding and processing, provides an audio and video signal transmission method and system based on software and hardware cooperation of an autonomous controllable architecture, and solves the problem of low bandwidth utilization rate. The method comprises the following steps: synchronously acquiring bandwidth fluctuation, packet loss rate and transmission delay parameters of a mobile terminal link, and generating a network state level through association analysis; performing resolution scaling on a brightness component of a video frame, performing dynamic downsampling on a chrominance component, generating a resolution reduction frame adaptive to a network state, and generating a fault-tolerant coding stream by combining a packet loss rate regulation and control quantization step size, a frame group length and an inter-frame prediction mode; performing entropy decoding and motion compensation to align brightness and chrominance components, forming a decoding reconstruction frame, performing multi-scale feature extraction and detail compensation, generating an enhanced brightness graph, and performing independent reconstruction on chrominance decoding components; and outputting an original resolution video frame through color reconstruction fusion. According to the invention, high-definition video low-delay transmission under network fluctuation is realized, and both bandwidth adaptability and image quality restoration precision are considered.

An example method of video processing includes: determining, for a conversion between a chroma block of a current processing unit of a current subpicture of a current picture of a video and a bitstream of the video, that a cross component adaptive loop filtering operation is applied to the chroma block, wherein the current picture comprises one or more subpictures; and performing the conversion based on the determining, wherein in the cross component adaptive loop filtering operation, a chroma sample of the chroma block is filtered based on information of luma samples, and wherein one or more luma samples located outside the current processing unit are excluded from the filtering of the chroma sample.

A method of decoding video data performed by an electronic device is provided. The method receives the video data and determines a block unit from a current frame included in the video data. The method determines a first chroma prediction block of the block unit based on a luma vector of the block unit, and determines a second chroma prediction block of the block unit using a cross-component filter based on a reconstructed luma block of the block unit. The method determines, from the video data, a weighting index for selecting, from multiple predefined parameters, multiple weighting parameters of the first chroma prediction block and the second chroma prediction block based on the weighting index. The method reconstructs the block unit based on the first chroma prediction block, the second chroma prediction block, and the weighting parameters.

Provided are an image fusion method, a storage medium and an electronic device are to-be-fused are acquired. Luminance and chrominance separation is performed on the visible light image to extract a luminance component and a chrominance component. Luminance fusion is performed on the luminance component of the visible light image and the infrared image to obtain a luminance fusion result. Image reconstruction is performed according to the luminance fusion result and the chrominance component of the visible light image to obtain a fused image.

An example device includes a memory configured to store video data; and a processing system comprising one or more processors implemented in circuitry and configured to: construct a merge candidate list for a current block of video data, wherein the processing system is configured to add a first merge candidate that was predicted using a first convolutional cross component model (CCCM) to the merge candidate list and add a second merge candidate that was predicted using a second CCCM to the merge candidate list, the first CCCM being different than the second CCCM; decode a merge index value for the current block of video data, the merge index value indicating the first merge candidate; in response to the merge index value indicating the first merge candidate, form a prediction block for the current block using the first CCCM; and decode the current block using the prediction block.

A method for signaling or parsing. for each chroma component of at least one portion of a picture. an information representative of a phase value between samples of the chroma component and samples of a luma component of the picture, the phase value being taken among at least three different phase values for each chroma component.

Methods for encoding a video sequence into a bitstream and decoding a bitstream to output one or more pictures for a video stream. An exemplary method includes: receiving a video sequence; encoding one or more pictures of the video sequence; and generating a bitstream associated with the encoded pictures, wherein the encoding comprises: predicting chroma samples within a current block based on luma samples corresponding to the chroma samples by a plurality of cross-component residual models (CCRMs).

The invention relates to the technical field of underwater image enhancement, and provides a deepwater image enhancement method based on multi-color space coupling, which comprises the following steps: determining an optimal channel, a moderate attenuation channel and a severe attenuation channel in an RGB color space based on a pixel average value, carrying out asymmetric histogram cutting pre-correction on the optimal channel, and carrying out deep-water image enhancement on the optimal channel; designing a loss function to enable an attenuation channel to approach an optimal channel through iterative compensation; in the Lab color space, clustering and segmenting the brightness component L into a plurality of pixel blocks by using an unsupervised pixel clustering model PCM, and performing local contrast enhancement and guided filtering-based noise reduction processing on each pixel block; and finally, carrying out nonlinear stretching on the chrominance components a and b by adopting a self-adaptive exponential function to improve the color naturalness. Through a multi-color space cooperative enhancement mechanism, the limitation of single color space processing in a traditional method is effectively solved, and the color correction precision, brightness enhancement and noise reduction balance and the naturalness optimization effect of the deep water image are improved.

The invention relates to the technical field of visual control, in particular to a picture defect test equipment control system and method, and the system comprises a difference tensor construction module, a space-time constraint construction module, a strain response judgment module, a coupling focusing mapping module and a boundary stability evaluation module. According to the method, the multi-dimensional difference incidence relation is constructed by extracting the pixel gray difference value, the brightness gradient and the chrominance phase angle, and fine brightness fluctuation and color shift in a picture can be captured. The superposition of the time-space change rate enables the dynamic performance of image defects to be distinguished, and continuous and transient anomalies can be effectively recognized. And in combination with tensor strain ratio and difference amplitude analysis, an abnormal region can be adaptively recognized, and neglect of a traditional method on a complex scene is avoided. The weighted aggregation of the local energy response improves the stability of the defect boundary, ensures the accurate positioning and judgment consistency of the image defect, and significantly improves the reliability and accuracy of the detection result especially in dynamic change and complex illumination environments.

A video decoding method is provided. The method comprises obtaining a coding unit in a current picture from a video bitstream, the coding unit comprising a luma block and at least one chroma block; and in response to determining that reconstructed luma samples in the luma block are not downsampled: determining one or more cross-component prediction models based on a luma filter, where the one or more cross-component prediction models include a convolutional cross-component model (CCCM); obtaining, based on the luma filter, at least one reconstructed luma sample in the luma block corresponding to a chroma sample in the at least one chroma block; and applying at least one of the one or more cross-component prediction models to the at least one reconstructed luma sample to predict the chroma sample.

Provided are an image encoding / decoding method and apparatus. An image decoding method may comprise deriving chroma reference samples located around a chroma block and luma reference samples corresponding to the chroma reference samples based on an intra prediction mode of the chroma block being a cross-component linear model (CCLM) mode, deriving CCLM parameters based on the chroma reference samples and the luma reference samples, and generating a prediction sample of the chroma block based on the CCLM parameters. The chroma reference samples may be obtained from two or more chroma reference lines adjacent to the chroma block.

A method and apparatus for processing video information comprises determining a chroma component prediction for a current block based on samples of a selected block, the block being selected in an area of decoded picture information based on a template matching process comprising a comparison of a template associated with the current block to at least one other template associated with at least one other block in an area of decoded picture information.

Methods for video decoding and encoding, apparatuses and non-transitory computer-readable storage media thereof are provided. In one method for video decoding, a decoder may obtain a motion compensated chroma sample and a plurality of motion compensated luma samples for a current inter coding block. Furthermore, the decoder may obtain an adaptive cross-component filter and obtain a filtered motion compensated chroma sample based on the adaptive cross-component filter, the motion compensated chroma sample, and the plurality of motion compensated luma samples.

A device for decoding encoded video data is configured to determine that a chroma block of the encoded video data is coded in a cross-component prediction (CCP) mode; generate a merge candidate list for the chroma block, wherein the merge candidate list includes at least two prediction candidates generated by different CCP modes and a third prediction candidate, wherein the third prediction candidate comprises a fusion prediction candidate; receive, in the encoded video data, a syntax element set to a value; select a prediction candidate from the merge candidate list based on the value of the syntax element; determine a prediction block for the chroma block based on the selected prediction candidate; determine a decoded block of video data based on the prediction block for the chroma block; and output a decoded picture of video data that includes the decoded block of video data.

The invention provides a MicroLED (Light Emitting Diode) display screen Demura preprocessing method and a MicroLED display screen Demura preprocessing system based on a color matrix. Acquiring brightness and chrominance distribution data of the MicroLED display panel based on the imaging type colorimeter; based on the data, performing accurate calculation through a compensation algorithm to obtain a compensation value of each pixel point; and the compensation values are applied to the display panel driving circuit, so that accurate compensation of the Mura phenomenon is realized. According to the method, the brightness and chrominance of the Mura data are automatically analyzed, the optimal compensation target value is determined, accurate compensation of the pixel level can be achieved through support of the Mura data and a compensation algorithm, the system can monitor input data of the display panel in real time and adjust the compensation value in real time, expandability is good, and the method is suitable for large-scale popularization and application. And the system can support MicroLED display panels with different sizes and resolution ratios, and the like. The system is mainly composed of a data acquisition processing module and a compensation value preprocessing calculation module.