GOLDEN-FRAME GROUP STRUCTURE DESIGN USING STILLNESS DETECTION

    公开(公告)号:US20190132592A1

    公开(公告)日:2019-05-02

    申请号:US15794134

    申请日:2017-10-26

    Applicant: GOOGLE LLC

    Abstract: Encoding a group of frames of a video sequence can include determining a stillness of the group of frames, in response to determining that the stillness of the group of frames meets stillness conditions, encoding the group of frames using a coding structure that is a one-layer coding structure, and, in response to determining that the stillness of the group of frames does not meet the stillness conditions, encoding the group of frames using the coding structure that is a multi-layer coding structure. Instructions for decoding a group of frames include instructions to determine, from an encoded bitstream, an indication of a coding structure used to encode the group of frames, receive the group of frames in a coding order of the coding structure, and decode the group of frames using the coding structure. The indication is one of a one-layer coding structure indication or a multi-layer coding structure indication.

    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.

    Golden-frame group structure design using stillness detection

    公开(公告)号:US10701364B2

    公开(公告)日:2020-06-30

    申请号:US15794134

    申请日:2017-10-26

    Applicant: GOOGLE LLC

    Abstract: Encoding a group of frames of a video sequence can include determining a stillness of the group of frames, in response to determining that the stillness of the group of frames meets stillness conditions, encoding the group of frames using a coding structure that is a one-layer coding structure, and, in response to determining that the stillness of the group of frames does not meet the stillness conditions, encoding the group of frames using the coding structure that is a multi-layer coding structure. Instructions for decoding a group of frames include instructions to determine, from an encoded bitstream, an indication of a coding structure used to encode the group of frames, receive the group of frames in a coding order of the coding structure, and decode the group of frames using the coding structure. The indication is one of a one-layer coding structure indication or a multi-layer coding structure indication.

    COMPOUND PREDICTION FOR VIDEO CODING

    公开(公告)号:US20220256186A1

    公开(公告)日:2022-08-11

    申请号:US17731470

    申请日:2022-04-28

    Applicant: GOOGLE LLC

    Abstract: Generating a compound predictor block for a current block of video includes generating, for the current block, a first predictor block using one of inter-prediction or intra-prediction and generating a second predictor block. The first predictor block includes a first pixel and the second predictor block includes a second pixel that is co-located with the first pixel. A first weight is determined for the first pixel using a difference between a value of the first pixel and a value of the second pixel. A second weight is determined for the second pixel using the first weight. The compound predictor block is generated by combining the first predictor block and the second predictor block. The compound predictor block includes a weighted pixel that is determined using a weighted sum of the first pixel and the second pixel using the first weight and the second weight.

    VIDEO COMPRESSION THROUGH MOTION WARPING USING LEARNING-BASED MOTION SEGMENTATION

    公开(公告)号:US20190261016A1

    公开(公告)日:2019-08-22

    申请号:US15898532

    申请日:2018-02-17

    Applicant: GOOGLE LLC

    Abstract: Regions for texture-based coding are identified using a spatial segmentation and a motion flow segmentation. For frames of a group of frames in a video sequence, a frame is segmented using a first classifier into at least one of a texture region or a non-texture region of an image in the frame. Then, the texture regions of the group of frames are segmented using a second classifier into a texture coding region or a non-texture coding region. The second classifier uses motion across the group of frames as input. Each of the classifiers is generated using a machine-learning process. Blocks of the non-texture region and the non-texture coding region of the current frame are coded using a block-based coding technique, while blocks of the texture coding region are coded using a coding technique that is other than the block-based coding technique.

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