Warped reference list for warped motion video coding

    公开(公告)号:US12267484B2

    公开(公告)日:2025-04-01

    申请号:US18074562

    申请日:2022-12-05

    Applicant: GOOGLE LLC

    Abstract: Encoding and decoding using warped reference list includes generating a reconstructed frame from an encoded bitstream by, for decoding a current block for the reconstructed frame, obtaining a dynamic reference list, obtaining a warped reference list, decoding a warped reference list index value, obtaining optimal predicted warped model parameters from the warped reference list in accordance with the index value, decoding differential warped model parameters, obtaining, as optimal warped model parameters, a result of adding the optimal predicted warped model parameters and the differential warped model parameters, obtaining predicted block data in accordance with the optimal warped model parameters, decoding residual block data, and obtaining, as decoded block data for the current block, a result of adding the residual block data and the predicted block data.

    ENTROPY CODING USING PRE-DEFINED, FIXED CDFS

    公开(公告)号:US20250088635A1

    公开(公告)日:2025-03-13

    申请号:US18803186

    申请日:2024-08-13

    Applicant: GOOGLE LLC

    Abstract: Entropy coding a sequence of transform coefficients includes determining a predictor value corresponding to a transform coefficient, selecting a probability model from a set of pre-defined probability models based on the predictor value, and entropy coding a symbol associated with the transform coefficient using the selected probability model. The predictor value can be calculated based on a previous predictor value used for coding an immediately preceding symbol associated with an immediately preceding transform coefficient of the sequence of the transform coefficients. The predictor value can be further calculated based on the immediately preceding symbol.

    Inter-prediction mode-dependent transforms for video coding

    公开(公告)号:US12143605B2

    公开(公告)日:2024-11-12

    申请号:US17543126

    申请日:2021-12-06

    Applicant: Google LLC

    Abstract: Transform modes are derived for inter-predicted blocks using side information. A prediction residual is generated for a current video block using a reference frame. Side information associated with one or both of the current video block or the reference frame is identified. A trained transform is determined from amongst multiple trained transforms based on the side information, in which each of the trained transforms is determined using individual side information types and combinations of the individual side information types and the side information represents values of one of the individual side information types or one of the combinations of the individual side information types. The prediction residual is transformed according to the trained transform, and data associated with the transformed prediction residual and the side information are encoded to a bitstream.

    Super-resolution loop restoration

    公开(公告)号:US12075081B2

    公开(公告)日:2024-08-27

    申请号:US18155224

    申请日:2023-01-17

    Applicant: Google LLC

    Abstract: A super-resolution coding mode is described. An encoded image can be decoded from an encoded bitstream stored on a non-transitory computer-readable storage medium. A flag can indicate whether an image was encoded using the super-resolution mode at a first resolution. Responsive to the flag indicating that the image was encoded using the super-resolution mode, bits indicating an amount of scaling of the image are included. The image is decoded from the encoded bitstream to obtain a reconstructed image at the first resolution, and the reconstructed image is upscaled to a second resolution using the amount of scaling to obtain an upscaled reconstructed image. The second resolution is higher than the first resolution. Loop restoration parameters within the bitstream can used for look restoration filtering of the upscaled reconstructed image to obtain a loop restored image at the second resolution.

    WARPED REFERENCE LIST FOR WARPED MOTION VIDEO CODING

    公开(公告)号:US20240187566A1

    公开(公告)日:2024-06-06

    申请号:US18074562

    申请日:2022-12-05

    Applicant: GOOGLE LLC

    CPC classification number: H04N19/105 H04N19/176 H04N19/182 H04N19/46

    Abstract: Encoding and decoding using warped reference list includes generating a reconstructed frame from an encoded bitstream by, for decoding a current block for the reconstructed frame, obtaining a dynamic reference list, obtaining a warped reference list, decoding a warped reference list index value, obtaining optimal predicted warped model parameters from the warped reference list in accordance with the index value, decoding differential warped model parameters, obtaining, as optimal warped model parameters, a result of adding the optimal predicted warped model parameters and the differential warped model parameters, obtaining predicted block data in accordance with the optimal warped model parameters, decoding residual block data, and obtaining, as decoded block data for the current block, a result of adding the residual block data and the predicted block data.

    Guided restoration of video data using neural networks

    公开(公告)号:US11282172B2

    公开(公告)日:2022-03-22

    申请号:US16515226

    申请日:2019-07-18

    Applicant: GOOGLE LLC

    Abstract: Guided restoration is used to restore video data degraded from a video frame. The video frame is divided into restoration units (RUs) which each correspond to one or more blocks of the video frame. Restoration schemes are selected for each RU. The restoration schemes may indicate to use one of a plurality of neural networks trained for the guided restoration. Alternatively, the restoration schemes may indicate to use a neural network and a filter-based restoration tool. The video frame is then restored by processing each RU according to the respective selected restoration scheme. During encoding, the restored video frame is encoded to an output bitstream, and the use of the selected restoration schemes may be signaled within the output bitstream. During decoding, the restored video frame is output to an output video stream.

    COMPOUND PREDICTION FOR VIDEO CODING

    公开(公告)号:US20210037254A1

    公开(公告)日:2021-02-04

    申请号:US17073892

    申请日:2020-10-19

    Applicant: GOOGLE LLC

    Abstract: Generating a compound predictor block of a current block of video can include generating, for the current block, predictor blocks comprising a first predictor block including first predictor pixels and a second predictor block including second predictor pixels; using at least a subset of the first predictor pixels to determine a first weight for a first predictor pixel of the first predictor pixels; obtaining a second weight for a second predictor pixel of the second predictor pixels, where the second predictor pixel is co-located with the first predictor pixel; and generating the compound predictor block by combining the first predictor block and the second predictor block, where the predictor block includes a weighted pixel that is determined using a weighted sum of the first predictor pixel and the second predictor pixel using the first weight and the second weight, respectively.

    IMAGE AND VIDEO CODING USING MACHINE LEARNING PREDICTION CODING MODELS

    公开(公告)号:US20200186796A1

    公开(公告)日:2020-06-11

    申请号:US16295176

    申请日:2019-03-07

    Applicant: GOOGLE LLC

    Abstract: Video coding may include generating, by a processor, a decoded frame by decoding a current frame from an encoded bitstream and outputting a reconstructed frame based on the decoded frame. Decoding includes identifying a current encoded block from the current frame, identifying a prediction coding model for the current block, wherein the prediction coding model is a machine learning prediction coding model from a plurality of machine learning prediction coding models, identifying reference values for decoding the current block based on the prediction coding model, obtaining prediction values based on the prediction coding model and the reference values, generating a decoded block corresponding to the current encoded block based on the prediction values, and including the decoded block in the decoded frame.

    GUIDED RESTORATION OF VIDEO DATA USING NEURAL NETWORKS

    公开(公告)号:US20200184603A1

    公开(公告)日:2020-06-11

    申请号:US16515226

    申请日:2019-07-18

    Applicant: GOOGLE LLC

    Abstract: Guided restoration is used to restore video data degraded from a video frame. The video frame is divided into restoration units (RUs) which each correspond to one or more blocks of the video frame. Restoration schemes are selected for each RU. The restoration schemes may indicate to use one of a plurality of neural networks trained for the guided restoration. Alternatively, the restoration schemes may indicate to use a neural network and a filter-based restoration tool. The video frame is then restored by processing each RU according to the respective selected restoration scheme. During encoding, the restored video frame is encoded to an output bitstream, and the use of the selected restoration schemes may be signaled within the output bitstream. During decoding, the restored video frame is output to an output video stream.

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