Adaptive filter intra prediction modes in image/video compression

    公开(公告)号:US10778972B1

    公开(公告)日:2020-09-15

    申请号:US16287969

    申请日:2019-02-27

    Applicant: GOOGLE LLC

    Abstract: A method for generating a prediction block for coding a block of a frame using intra prediction. The method includes determining, using a training region, filter coefficients for generating the prediction block, the training region neighbors the block and includes a plurality of reconstructed pixels, the filter coefficients minimize a function of differences, each difference being a respective difference between a pixel in the training region and a prediction of that pixel in the training region, and the predictions use the filter coefficients; and generating the prediction block using the determined filter coefficients.

    Entropy coding in image and video compression using machine learning

    公开(公告)号:US10652581B1

    公开(公告)日:2020-05-12

    申请号:US16287889

    申请日:2019-02-27

    Applicant: GOOGLE LLC

    Abstract: Machine learning is used to refine a probability distribution for entropy coding video or image data. A probability distribution is determined for symbols associated with a video block (e.g., quantized transform coefficients, such as during encoding, or syntax elements from a bitstream, such as during decoding), and a set of features is extracted from video data associated with the video block and/or neighbor blocks. The probability distribution and the set of features are then processed using machine learning to produce a refined probability distribution. The video data associated with a video block are entropy coded according to the refined probability distribution. Using machine learning to refine the probability distribution for entropy coding minimizes the cross-entropy loss between the symbols to entropy code and the refined probability distribution.

    Palette Mode Coding With Designated Bit Depth Precision

    公开(公告)号:US20240305802A1

    公开(公告)日:2024-09-12

    申请号:US18276407

    申请日:2021-02-09

    Applicant: Google LLC

    CPC classification number: H04N19/44 H04N19/14 H04N19/176 H04N19/186

    Abstract: Syntax elements are written to a bitstream to designate bit depth precision for palette mode coding of video blocks. During encoding, a bit depth to use for palette mode coding a current block may be based on an input video signal including the current block or based on some change in bit depth precision. A prediction residual for the current block is encoded to a bitstream along with syntax elements indicative of the bit depth used for the palette mode coding of the current block. In particular, the syntax elements include a first element indicating the palette mode coding bit depth used and a second element indicating whether to apply a bit offset to the palette mode coding bit depth. During decoding, values of the syntax elements are read from the bitstream and used to determine a bit depth for palette mode coding the encoded block.

    Adaptive filter intra prediction modes in image/video compression

    公开(公告)号:US11979564B2

    公开(公告)日:2024-05-07

    申请号:US17684461

    申请日:2022-03-02

    Applicant: GOOGLE LLC

    CPC classification number: H04N19/11 H04N19/117 H04N19/184

    Abstract: Generating a prediction block for coding a block includes determining an adaptive intra-prediction mode indicative of at least a training region and a configuration of neighboring pixel locations. The training region neighbors the block and includes a plurality of reconstructed pixels. Filter coefficients are obtained. The filter coefficients are used to obtain respective prediction pixels of neighboring pixels within the training region when applied to defined respective configurations of the neighboring pixels according to the configuration of the neighboring pixels. The filter coefficients minimize a function of differences, each difference being a respective difference between a pixel in the training region and a prediction of that pixel in the training region. The prediction block is generated by recursive extrapolations that use the filter coefficients by predicting each pixel of the prediction block by applying the filter coefficients to the configuration of neighboring pixels for the pixel being predicted.

    ADAPTIVE FILTER INTRA PREDICTION MODES IN IMAGE/VIDEO COMPRESSION

    公开(公告)号:US20220191479A1

    公开(公告)日:2022-06-16

    申请号:US17684461

    申请日:2022-03-02

    Applicant: GOOGLE LLC

    Abstract: Generating a prediction block for coding a block includes determining an adaptive intra-prediction mode indicative of at least a training region and a configuration of neighboring pixel locations. The training region neighbors the block and includes a plurality of reconstructed pixels. Filter coefficients are obtained. The filter coefficients are used to obtain respective prediction pixels of neighboring pixels within the training region when applied to defined respective configurations of the neighboring pixels according to the configuration of the neighboring pixels. The filter coefficients minimize a function of differences, each difference being a respective difference between a pixel in the training region and a prediction of that pixel in the training region. The prediction block is generated by recursive extrapolations that use the filter coefficients by predicting each pixel of the prediction block by applying the filter coefficients to the configuration of neighboring pixels for the pixel being predicted.

    Entropy coding in image and video compression using machine learning

    公开(公告)号:US11259053B2

    公开(公告)日:2022-02-22

    申请号:US16838539

    申请日:2020-04-02

    Applicant: GOOGLE LLC

    Abstract: Machine learning is used to refine a probability distribution for entropy coding video or image data. A probability distribution is determined for symbols associated with a video block (e.g., quantized transform coefficients, such as during encoding, or syntax elements from a bitstream, such as during decoding), and a set of features is extracted from video data associated with the video block and/or neighbor blocks. The probability distribution and the set of features are then processed using machine learning to produce a refined probability distribution. The video data associated with a video block are entropy coded according to the refined probability distribution. Using machine learning to refine the probability distribution for entropy coding minimizes the cross-entropy loss between the symbols to entropy code and the refined probability distribution.

    ADAPTIVE FILTER INTRA PREDICTION MODES IN IMAGE/VIDEO COMPRESSION

    公开(公告)号:US20200382773A1

    公开(公告)日:2020-12-03

    申请号:US16999109

    申请日:2020-08-21

    Applicant: GOOGLE LLC

    Abstract: A processor decodes, from a compressed bitstream, an adaptive intra-prediction mode of a set of adaptive filter modes, the adaptive intra-prediction mode indicating a number of filter coefficients and relative locations with respect to a to-be-predicted pixel of a sub-set of neighboring pixels of the to-be-predicted pixel; determines filter coefficients for generating a prediction block of the block; and generates, by recursive extrapolations that use the filter coefficients and the relative locations, the prediction block. The set of adaptive filter modes includes a first adaptive mode and a second adaptive mode. The first adaptive mode and the second adaptive mode indicate a same number of coefficients. The first adaptive mode indicates a first set of first relative locations of a first sub-set of neighboring pixels that is different from a second set of second relative locations of a second sub-set of neighboring pixels indicated by the second adaptive mode.

    ADAPTIVE FILTER INTRA PREDICTION MODES IN IMAGE/VIDEO COMPRESSION

    公开(公告)号:US20240267514A1

    公开(公告)日:2024-08-08

    申请号:US18635416

    申请日:2024-04-15

    Applicant: GOOGLE LLC

    CPC classification number: H04N19/11 H04N19/117 H04N19/184

    Abstract: A compressed bitstream is configured for decoding by operations that include identifying an adaptive intra-prediction mode indicative of at least a training region or a configuration of neighboring pixel locations. The training region neighbors a block and consists of reconstructed pixels. Filter coefficients used to obtain respective prediction pixels of neighboring pixels within the training region when applied according to the configuration of the neighboring pixels are determined. The filter coefficients minimize a function of differences. Each difference is a respective difference between a pixel in the training region and a prediction of that pixel in the training region. A prediction block is generated for the block by recursive extrapolations that use the filter coefficients by predicting each pixel of the prediction block by applying the filter coefficients to the configuration of neighboring pixels for the pixel being predicted.

    Adjustable per-symbol entropy coding probability updating for image and video coding

    公开(公告)号:US10951921B2

    公开(公告)日:2021-03-16

    申请号:US16776863

    申请日:2020-01-30

    Applicant: GOOGLE LLC

    Inventor: Yaowu Xu Hui Su

    Abstract: Generating encoded image data using adjustable per-symbol entropy coding probability updating may include generating a portion of the encoded image data in accordance with a value of a probability update indicator for the portion indicating whether per-symbol entropy coding probability updating is disabled for the portion, and including the value of the probability update indicator and the entropy coded image data in an output bitstream. Generating decoded image data using adjustable per-symbol entropy coding probability updating may include obtaining a value of a probability update indicator for a portion of the decoded image data, the value of the probability update indicator for the portion indicating whether per-symbol entropy coding probability updating is disabled for the portion, and generating decoded image data for the portion in accordance with the value of the probability update indicator for the portion.

Patent Agency Ranking