Abstract: A learning model is trained for rate-distortion behavior prediction against a corpus of a video hosting platform and used to determine optimal bitrate allocations for video data given video content complexity across the corpus of the video hosting platform. Complexity features of the video data are processed using the learning model to determine a rate-distortion cluster prediction for the video data, and transcoding parameters for transcoding the video data are selected based on that prediction. The rate-distortion clusters are modeled during the training of the learning model, such as based on rate-distortion curves of video data of the corpus of the video hosting platform and based on classifications of such video data. This approach minimizes total corpus egress and/or storage while further maintaining uniformity in the delivered quality of videos by the video hosting platform.

Abstract: An encoder that encodes a video includes a processor and memory. Using the memory, the processor: derives a prediction error of an image included in the video, by subtracting a prediction image of the image from the image; determines a secondary transform basis based on a primary transform basis, the primary transform basis being a transform basis for a primary transform to be performed on the prediction error, the secondary transform basis being a transform basis for a secondary transform to be performed on a result of the primary transform; performs the primary transform on the prediction error using the primary transform basis; performs the secondary transform on a result of the primary transform using the secondary transform basis; performs quantization on a result of the secondary transform; and encodes a result of the quantization as data of the image.

Abstract: The present invention relates to an image encoding/decoding method and apparatus. An image encoding method according to the present invention may comprise generating a transform block by performing at least one of transform and quantization; grouping at least one coefficient included in the transform block into at least one coefficient group (CG); scanning at least one coefficient included in the coefficient group; and encoding the at least one coefficient.

Abstract: An encoded bitstream of entropy encoded video data is received by a video decoder. The encoded bitstream represents syntax elements of a sequence of coding blocks. The sequence of coding blocks is recovered by processing a bin sequences associated with each coding block in a processing pipeline, wherein a defined amount of time is allocated to process each coding block in the processing pipeline. The encoded bitstream is arithmetically decoded to produce each bin sequence. The arithmetic decoder is time-wise decoupled from the processing pipeline by storing a plurality of the bin sequences in a buffer memory.

Abstract: A method for decoding a digital image from encoded data representative of the image. The image is divided into blocks processed in a defined order. The method includes, for a current block having a predetermined number (Mv) of lines and number (Mh) of columns: decoding coefficients of the current block from coded data; decoding an index representative of an identifier of a transform among a plurality of transforms and identifying the transform, a transform being expressed as a vertical subtransform of size Mv*Mv and a horizontal subtransform of size Mh*Mh; transforming the current block into a decoded block transformed, from the transform obtained, by successive application of the vertical subtransform and then the horizontal subtransform or respectively of the horizontal subtransform and then the vertical subtransform; and reconstructing the image from the transformed decoded block. The transforming includes: a modified use of core sub-transform coefficients, their absolute values being retained.

Abstract: A method for video processing is provided. The method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on two or four chroma samples and/or corresponding luma samples; and performing the conversion based on the determining.

Abstract: According to embodiments described herein, sub-pictures and/or virtual boundaries can be used for coding an image. For example, sub-pictures in the current picture can be used for predicting, reconstructing, and/or filtering the current picture. Virtual boundaries can be used for filtering reconstructed samples of the current picture. Through image coding based on the subpictures and/or virtual boundaries according to embodiments described herein, the subjective/objective quality of an image can be improved, and the consumption of hardware resources necessary for the coding can be reduced.

Abstract: Improved techniques for generating video content are disclosed. In some embodiments, it is determined whether a frame comprising a scene is an independent frame or a predictive frame. In the event that the frame is an independent frame, the frame is encoded independently. In the event that the frame is a predictive frame, block differences and motion vectors are encoded, wherein motion vectors are determined from a known three-dimensional model and time evolution of the scene.

Abstract: The present invention includes: a CCLM prediction derivation portion, for deriving a first parameter and a second parameter by using a sampled luminance value downsampled according to a chrominance format and an intra-frame prediction mode; and a CCLM prediction filter portion, for deriving a prediction image by using the first parameter and the second parameter, wherein the CCLM prediction derivation portion derives the first parameter by deriving a logarithmic value of a luminance difference value, deriving a first value by right-shifting a second value related to the luminance difference value by the logarithmic value, and using a third value acquired by multiplying a fourth value by a chrominance difference value and derives the second parameter by using the first parameter. The fourth value is determined from a reference table by using the first value.

Abstract: Methods and apparatus for predicting a future estimated host read access rate for variable bit rate (VBR) data streams that include Program Clock Reference (PCR) indicators or other playback clock synchronization values. The VBR data stream may be encoded, for example, as a Motion Picture Experts Group (MPEG)-transport stream (TS). In some examples, a data storage device with a non-volatile memory (NVM) array parses an MPEG-TS VBR data stream retrieved from the NVM array to identify PCRs. Using the PCRs, the device estimates the future host data access rate for additional portions of MPEG-TS VBR data not yet requested by the host. The data storage device may then adaptively adjust background (e.g. overhead) management operations such as garbage collection based on the future host data access rate.

Abstract: The data processing method and system provided in the present specification may use a first transfer function to perform an encoding spectrum-adjustment on an original frame in original data when compressing the original data, so that the amplitude of the intermediate-frequency to high-frequency region in the original frame may be smoothly reduced, thereby reducing the data information in the original frame and improve the encoding efficiency. Thus, the compressed data volume is reduced. When the method and system are employed to decompress a compressed frame, a second transfer function may be used to perform a decoding spectrum-adjustment on the compressed frame, where the second transfer function corresponds to the first transfer function, so as to restore the data in the compressed frame and obtain a decompressed frame. The method and system may improve data compression efficiency and transmission efficiency.

Abstract: New systems and methods allow for transmission of multiple types of content protocols over a unidirectional content delivery network, such as a television broadcast. Hardware and/or software used at the network transmission location (such as a television broadcast station) and hardware and/or software located at an endpoint (such as a home television, car infotainment system, or first responder location) allow for a native ATSC 1.0 signal to have embedded within it additional content that is not encoded as ATSC 1.0 content. The non-ATSC 1.0 content can be detected and segregated from ATSC 1.0 content so that the endpoint devices (such as a television receiver) will not attempt to render the non-ATSC 1.0 content (such as, e.g., ATSC 3.0 content or application specific content) as normal ATSC 1.0 programming. Instead, the non-ATSC 1.

Abstract: A video codec uses fractional increments of quantization step size at high bit rates to permit a more continuous variation of quality and/or bit rate as the quantization scale changes. For high bit rate scenarios, the bit stream syntax includes an additional syntax element to specify fractional step increments (e.g., half step) of the normal quantizer scale step sizes.

Abstract: A video decoder receives data from a bitstream for a block of pixels to be decoded as a current block of a current picture of a video. The video decoder receives from the bitstream first and second signaled indices for the current block. The video decoder determines first and second merge indices from the first and second signaled indices. The video decoder uses the first and second merge indices to select first and second motion candidates, respectively. The video decoder generates a set of prediction samples in ALWIP mode and performs an inverse secondary transform and an inverse primary transform to generate a set of residual samples of the current block. Enabling or selection of secondary transform and/or primary transform depends on size, width, and/or height for the current block. The video decoder reconstructs the current block by using the set of residual samples and the set of prediction samples.

Abstract: An example device for coding video data includes a memory configured to store video data; and one or more processing units implemented in circuitry and configured to: store motion information for a first coding tree unit (CTU) line of a picture in a first history motion vector predictor (MVP) buffer of the memory; reset a second history MVP buffer of the memory; and after resetting the second history MVP buffer, store motion information for a second CTU line of the picture in the second history MVP buffer, the second CTU line being different than the first CTU line. Separate threads of a video coding process executed by the one or more processors may process respective CTU lines, in some examples.

Abstract: In general, encoding or decoding a picture part can involve determining a spatiotemporal motion vector predictor (STMVP) candidate for a merge mode of operation from spatial motion vector candidates taken from spatial positions around a current coding unit (CU) and a temporal motion vector candidate, where at least one embodiment involves determining the STMVP candidate based on considering at most two spatial positions and based on an average of at least two of the spatial and temporal motion vector candidates.

Abstract: A method for video processing is provided. The method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on two or four chroma samples and/or corresponding luma samples; and performing the conversion based on the determining.

Abstract: An encoder may perform a dynamic encoding that adapts the encoding of hyperspectral data according to the number of bands of the electromagnetic spectrum that are captured by different imaging devices, the amount of data that is contained in each band, and/or encoding criteria that are specified by a user or that are automatically generated by the encoder for an optimal encoding of the hyperspectral data. The encoder may receive hyperspectral data for different electromagnetic spectrum bands. The encoder may determine an encoding resolution based on one or more of a number of bands and a maximum resolution within the received bands. The encoder may configure a block size for a file format that is used to store an encoding of the hyperspectral data based on the encoding resolution, and may encode the hyperspectral data contained within each band to at least one block of the block size.

Abstract: An encoder includes circuitry configured to receive a video frame, partition the video frame into a plurality of blocks, determine a respective spatial activity measure for each block in the plurality of blocks and using a transform matrix, encode the video frame using the spatial activity measure. Related apparatus, systems, techniques and articles are also described.

Abstract: An image decoding method according to the present invention can comprise the steps of: acquiring residual coefficients of a current block; dequantizing the residual coefficients; performing secondary inverse transformation on the dequantized residual coefficients; and performing primary inverse transformation on the performance result of the secondary inverse transformation. The secondary inverse transformation can be performed for a partial region of the current block.

Abstract: A method of encoding video data, the method comprising: generating prediction data of the video data; generating residual data based on the prediction data and digital sample values of the video data; generating coefficients based on the residual data; performing an interlacing process to generate an interlaced amplitude value, wherein the interlacing process interlaces bits of two or more of the coefficients to generate the interlaced amplitude value; modulating an analog signal based on the interlaced amplitude value; generating digital values based on the prediction data; and outputting the analog signal and digital values based on the prediction block.

Abstract: A time-series-data feature extraction device includes: a data processing unit that processes a received unevenly spaced time-series-data group into an evenly spaced time-series-data group including omissions and an omission information group indicating presence or absence of omissions, based on a received input time-series data length and a received minimum observation interval; a model learning unit that learns a weight vector of each layer of a model with a difference between an element not missing in a matrix of the evenly spaced time-series-data group including omissions and an element of an output result of an output layer of the model being taken as an error, and stores the weight vector as a model parameter in a storage unit, the difference being; and a feature extraction unit that receives time-series data of a feature extraction target, calculates a value of the intermediate layer of the model with use of the model parameter stored in the storage unit by inputting the received time-series data of the

Abstract: Techniques are provided for determining variance of a pixel block in a frame of video based on variance of pixel blocks in a reference frame of the video, instead of directly, for example, by calculating variance based on pixel values of the pixel block. The techniques include identifying a motion vector for a pixel block in a current frame, the motion vector pointing to a pixel block in a reference frame. The techniques also include determining the cost associated with the motion vector and comparing the cost to first and second thresholds. The techniques include determining the variance for the pixel block of the current frame based on the comparison of the cost to the first and second threshold and based on the variance of the pixel block of the reference frame.

Abstract: A coefficient conversion unit obtains a conversion coefficient for each image region by performing coefficient conversion for each image region. A luminance distribution extraction unit generates luminance distribution information indicating a luminance of each image region. A correction coefficient determination unit determines a correction coefficient based on the luminance distribution information for each image region. A quantization width correction unit obtains a corrected quantization width for each image region by correcting a quantization width with use of a correction coefficient of an image region for each image region. A scalar quantization unit obtains a quantized conversion coefficient for each image region by quantizing a conversion coefficient of an image region with use of a corrected quantization width for each image region.

Abstract: An example device for processing image data includes a memory configured to store an image; and one or more processors implemented in circuitry and configured to: process the image to identify a pilot signal in the image indicating a portion of the image, the pilot signal forming a boundary around the portion and having pixel values defined according to a mathematical relationship with pixel values within the portion such that the pilot signal is not perceptible to a human user and is detectable the device; determine the portion of the image using the pilot signal; and further process the portion to attempt to detect one or more contents of the portion without attempting to detect the one or more contents of the image in portions of the image outside the portion.

Abstract: Methods and apparatuses for image encoding and image decoding are provided. The image decoding method includes: obtaining deep neural network (DNN) update permission information indicating whether one or more pieces of DNN setting information are updated; based on the DNN update permission information indicating that the one or more pieces of the DNN setting information are updated, obtaining DNN update information necessary for determining one or more pieces of the DNN setting information that are updated; determining the one or more pieces of the updated DNN setting information according to the DNN update information; and obtaining a third image by performing artificial intelligence (AI) up-scaling on a second image according to the one or more pieces of the updated DNN setting information.

Abstract: The present disclosure relates to a method for compensating an image. The method comprises estimating transform coefficients of a frequency component for a first image based on the first image, performing a dot multiplication operation between the estimated transform coefficients and a basis function associated with the frequency component to generate a compensation image, and combining the first image and the compensation image to generate a combined image.

Abstract: The present disclosure relates to motion vector determination using template or bilateral matching and predictor generation based on the motion vector. The template or bilateral matching and/or the predictor generation use interpolation filtering. The interpolation filtering operation accesses integer sample positions within a window, and further uses padded sample values for integer sample positions outside the window, which are based on at least one sample within said window, and uses the accessed integer sample position values as well as the padded sample values to perform the template or bilateral matching and/or predictor generation.

Abstract: A stain compensation method using a screen calibration system includes generating first parameter data including first data blocks, each defined by at least one emission area, by photographing a display surface, generating second parameter data including second data blocks, the second data blocks being generated by merging first data blocks that are adjacent to each other in one direction and have an identical average grayscale value, and storing the second parameter data in a memory.

Abstract: The present disclosure relates to an apparatus and a method for image processing each of which enables reduction of a coding efficiency to be suppressed. In the case where primary transformation as transformation processing for a predictive residue as a difference between an image and a predictive image of the image and secondary transformation as transformation processing for a primary transformation coefficient obtained by subjecting the predictive residue to the primary transformation are caused to be skipped, a switch also causes bandwidth limitation for a secondary transformation coefficient obtained by subjecting the primary transformation coefficient to the secondary transformation to be skipped. The present disclosure, for example, can be applied to an image processing apparatus, an image coding apparatus, an image decoding apparatus or the like.

Abstract: Methods and apparatus for compressing data streams. In an embodiment, a method includes calculating a decomposition of matrix data to generate eigenvectors and associated eigenvalues, determining clusters of the eigenvectors based on weighting the eigenvalues, calculating an eigenvector centroid for each cluster so that a dictionary of centroids is generated, and tagging the eigenvectors with tags, respectively, that identify an associated eigenvector centroid for each eigenvector.

Abstract: The invention provides methods that improve image compression and/or quality within the JPEG process by using a low-pass filter to remove high frequency components from image data, which removes blocking artifacts. Preferred embodiments apply the low-pass filter to the Chroma components after decompression prior to conversion into RGB color space.

Abstract: The present disclosure provides a method for reconstructing a video signal through a low-complexity Discrete Sine Transform-7 (DST7) design, including: obtaining a transform index of a current block from the video signal, wherein the transform index corresponds to any one of a plurality of transform combinations including combinations of DST7 and/or a Discrete Cosine Transform-8 (DCT8); deriving a transform combination corresponding to the transform index, wherein the transform combination includes a horizontal transform and a vertical transform, and wherein the horizontal transform and the vertical transform correspond to any one of the DST7 and the DCT8; performing an inverse transform on the current block in a vertical or horizontal direction using the DST7 or the DCT8; and reconstructing the video signal using the inverse transformed current block, wherein a 33-point Discrete Fourier Transform (DFT) is applied to the DST7 when the DST7 is 16×16 and a 65-point DFT is applied to the DST7 when the DST7 is 32

Abstract: A video codec uses fractional increments of quantization step size at high bit rates to permit a more continuous variation of quality and/or bit rate as the quantization scale changes. For high bit rate scenarios, the bit stream syntax includes an additional syntax element to specify fractional step increments (e.g., half step) of the normal quantizer scale step sizes.

Abstract: A method and apparatus for video encoding or decoding performed by a video encoder or a video decoder incorporating advanced multiple transform (AMT) are disclosed. According to this method receives input data associated with a current block, wherein the input data corresponds to a current coefficient block to be processed by an inverse transform process, and determines a default transform type and a single transform set consisting of two transform types. The method then selects a vertical transform and a horizontal transform from the default transform type or the single transform set based on at least a transform selection flag, wherein the transform selection flag is decoded after decoding transform coefficients of the current block, and recovers the current block according to the current coefficient block, a vertical inverse transform associated with the vertical transform and a horizontal inverse transform associated with the horizontal transform.

Abstract: As described herein, a system, method, and computer program are provided for edge management of geographically dispersed sensors. An edge device within a network accesses observations of a plurality of geographically dispersed sensors. Additionally, the edge device processes the observations to determine overlapping portions of the observations. Further, the edge device optimizes the observations to form optimized observations for transmission to a cloud processing system, wherein the optimizing is based on the determined overlapping portions of the observations.

Abstract: This application relates to a video decoding method performed at a computer device. The method includes: obtaining encoded data corresponding to a current video frame; obtaining a processing parameter corresponding to the current video frame; determining a target processing manner corresponding to the current video frame according to the processing parameter, the target processing manner being one of candidate processing manners, the candidate processing manners comprising at least one of a full resolution processing manner and a downsampling processing manner, and the processing parameter being consistent with a corresponding processing parameter in an encoding process; and decoding the encoded data corresponding to the current video frame according to the target processing manner, to obtain a corresponding decoded video frame. In the encoding method, a processing manner for a video frame can be flexibly selected, thereby improving video encoding quality in the case of limited bandwidth.

Abstract: Disclosed in the present specification is a method for performing channel encoding. The method can comprise the steps of: interleaving information bits; and encoding the interleaved information bits by using a polar code. The information bits can be interleaved according to an interleaving pattern.

Abstract: Techniques are disclosed by which a coding parameter is determined to encode video data resulting in encoded video data possessing a highest possible video quality. Features may be extracted from an input video sequence. The extracted features may be compared to features described in a model of coding parameters generated by a machine learning algorithm from reviews of previously-coded videos, extracted features of the previously-coded videos, and coding parameters of the previously-coded videos. When a match is detected between the extracted features of the input video sequence and extracted features represented in the model, a determination may be made as to whether coding parameters that correspond to the matching extracted feature correspond to a tier of service to which the input video sequence is to be coded.

Abstract: A method for decoding a digital image from encoded data representative of the image. The image is divided into blocks processed in a defined order. The method includes, for a current block having a predetermined number (Mv) of lines and number (Mh) of columns: decoding coefficients of the current block from coded data; decoding an index representative of an identifier of a transform among a plurality of transforms and identifying the transform, a transform being expressed as a vertical subtransform of size Mv*Mv and a horizontal subtransform of size Mh*Mh; transforming the current block into a decoded block transformed, from the transform obtained, by successive application of the vertical subtransform and then the horizontal subtransform or respectively of the horizontal subtransform and then the vertical subtransform; and reconstructing the image from the transformed decoded block. The transforming includes: a modified use of core sub-transform coefficients, their absolute values being retained.

Abstract: A method of compressing image data that comprise a plurality of pixel values that are associated with a respective pixel is described, wherein the pixel values are compressed for at least some pixels in accordance with the following steps: associating the respective pixel with one of a plurality of pixel groups in accordance with a predetermined grouping scheme, with each of the plurality of pixel groups being defined by the pixels of a plurality of predetermined pixel alignments or by a subset of pixels of a plurality of predetermined pixel alignments; determining an estimated pixel value of the respective pixel in dependence on the pixel value of at least one predetermined other pixel while using at least one estimation rule, with the at least one predetermined other pixel being selected in dependence on the pixel group of the respective pixel; forming a difference value of the respective pixel that corresponds to a predetermined relation between the pixel value and the estimated pixel value of the respecti

Abstract: Described tools and techniques relate to signaling for DC coefficients at small quantization step sizes. The techniques and tools can be used in combination or independently. For example, a tool such as a video encoder or decoder processes a VLC that indicates a DC differential for a DC coefficient, a FLC that indicates a value refinement for the DC differential, and a third code that indicates the sign for the DC differential. Even with the small quantization step sizes, the tool uses a VLC table with DC differentials for DC coefficients above the small quantization step sizes. The FLCs for DC differentials have lengths that vary depending on quantization step size.

Abstract: An electronic device and a method for controlling the same include inputting an input image into an artificial intelligence model, acquiring a feature map for the input image, converting the feature map through a lookup table corresponding to the feature map, and storing the converted feature map by compressing the feature map through a compression mode corresponding to the feature map.

Abstract: A method and a device for processing a video signal are disclosed. In particular, a method for decoding a video signal includes parsing a first syntax element indicating a primary transform kernel applied to a primary transform of a current block; determining whether a secondary transform is applicable to the current block based on the first syntax element; if the secondary transform is applicable to the current block, parsing a second syntax element indicating a secondary transform kernel applied to a secondary transform of the current block; deriving a secondary inverse-transformed block, by performing a secondary inverse-transform for a top-left specific region of the current block using a secondary transform kernel indicated by the second syntax element; and deriving a residual block of the current block, by performing a primary inverse-transform for the secondary inverse-transformed block using a primary transform kernel indicated by the first syntax element.

Abstract: A method and apparatus of priority-based MVP (motion vector predictor) derivation for motion compensation in a video encoder or decoder are disclosed. According to this method, one or more final motion vector predictors (MVPs) are derived using priority-based MVP derivation process. The one or more final MVPs are derived by selecting one or more firstly available MVs from a priority-based MVP list for Inter prediction mode, Skip mode or Merge mode based on reference data of one or two target reference pictures that are reconstructed prior to the current block according to a priority order. Therefore, there is no need for transmitting information at the encoder side nor deriving information at the decoder side that is related to one or more MVP indices to identify the one or more final MVPs in the video bitstream.

Abstract: Systems, apparatuses, and methods for implementing spatial block-level pixel activity extraction optimization leveraging motion vectors are disclosed. Control logic coupled to an encoder generates block-level pixel activity metrics for a new frame based on the previously calculated block-level pixel activity data from a reference frame. A cost is calculated for each block of a new frame with respect to a corresponding block of the reference frame. If the cost is less than a first threshold, then the control logic generates an estimate of a pixel activity metric for the block which is equal to a previously calculated pixel activity metric for a corresponding block of the reference frame. If the cost is greater than the first threshold but less than a second threshold, an estimate of the pixel activity metric is generated by extrapolating from the previously calculated pixel activity metric.

Abstract: An encoder may determine a plurality of coding units associated with a frame of a media file and a plurality of prediction units associated with the frame of the media file. The encoder may determine, based on the plurality of coding units associated with the frame and the plurality of prediction units associated with the frame, and based on a training of the encoder using one or more neural networks, that a particular region of the frame can be encoded using one or more encoding characteristics that are different than the encoding characteristics of one or more other particular regions of the frame. The encoder may allocate one or more encoding resources to the particular region of the frame based on the one or more encoding characteristics of the particular region of the frame in order to reduce the overall media bitrate.

Abstract: A video codec uses fractional increments of quantization step size at high bit rates to permit a more continuous variation of quality and/or bit rate as the quantization scale changes. For high bit rate scenarios, the bit stream syntax includes an additional syntax element to specify fractional step increments (e.g., half step) of the normal quantizer scale step sizes.

Abstract: A method for video processing is provided. The method includes determining, for a conversion between a current video block of a video that is a chroma block and a coded representation of the video, parameters of a cross-component linear model (CCLM) based on two or four chroma samples and/or corresponding luma samples; and performing the conversion based on the determining.

Abstract: Implementations disclose zero-copy adaptive bitrate video streaming. A method includes capturing, by a user device, a first video frame of a plurality of video frames of a video item to be transmitted as a livestream; delivering the first video frame to an encoder of the user device; capturing a second video frame of the plurality of video frames, the second video frame being captured after the first video frame; delivering the second video frame to the encoder of the user device; in response to determining that the first video frame did not enter the encoder prior to the second video frame arriving at the encoder, discarding the first video frame; determining, by the user device, a frequency of discarded video frames comprising the first video frame; and adjusting, by a processing device of the user device, quality of the video item transmitted as the livestream based on the frequency.