Restoration in video coding using domain transform recursive filters

    公开(公告)号:US10757408B2

    公开(公告)日:2020-08-25

    申请号:US15789400

    申请日:2017-10-20

    Applicant: GOOGLE LLC

    Abstract: Restoring a degraded tile of a degraded frame resulting from reconstruction is disclosed. A method includes, for a scaling factor of at least some scaling factors, recursively filtering the degraded tile using the scaling factor to generate a respective restored tile, and determining a respective error for the respective restored tile with respect to the source tile. The method also includes selecting an optimal scaling factor from the at least some scaling factors and encoding, in an encoded bitstream, a scaling parameter based on the optimal scaling factor. The optimal scaling factor corresponding to a smallest respective error. An apparatus includes a processor and non-transitory memory storing instructions. The instructions cause the processor to determine, from an encoded bitstream, a scaling factor, which determines how strongly edges in the degraded tile affect filtering operations, and recursively filter, resulting in a restored tile, the degraded tile using the scaling factor.

    Warped reference motion vectors for video compression

    公开(公告)号:US10582212B2

    公开(公告)日:2020-03-03

    申请号:US15846295

    申请日:2017-12-19

    Applicant: GOOGLE LLC

    Abstract: A motion vector candidate list is generated that can be used to encode or decode a motion vector used to predict the current block. A motion mode and motion information for a source block is determined. A motion vector used to predict the source block is added to the list responsive to determining that the motion mode for the source block is a translational motion mode and that a reference frame for the source block matches the reference frame for the current block. A warped reference motion vector is instead added to the list responsive to determining that the motion mode for the source block is a warped motion mode and that the reference frame for the source block matches the reference frame for the current block. A reference motion vector from the list is selected for encoding or decoding the current block motion vector.

    Multi-level compound prediction
    75.
    发明授权

    公开(公告)号:US10555000B2

    公开(公告)日:2020-02-04

    申请号:US16434339

    申请日:2019-06-07

    Applicant: GOOGLE LLC

    Abstract: Coding a current block using multi-level compound predictor is disclosed. An apparatus includes a memory and a processor. The processor is configured to execute instructions stored in the memory to generate four or more prediction blocks; combine a first prediction block and a second prediction block of the four or more prediction blocks to form a first first-level compound prediction block; combine a third prediction block and a fourth prediction block of the four or more prediction blocks to form a second first-level compound prediction block; and combine, to obtain a prediction block for coding the current block, the first first-level compound prediction block and the second first-level compound prediction block.

    INTRA-PREDICTION FOR SMOOTH BLOCKS IN IMAGE/VIDEO

    公开(公告)号:US20190335199A1

    公开(公告)日:2019-10-31

    申请号:US15966005

    申请日:2018-04-30

    Applicant: GOOGLE LLC

    Abstract: Coding a block of a video frame using an intra-prediction mode is disclosed. A method includes selecting first neighboring pixels, generating second pixels for use along a second edge that is opposite the first edge of the block, and generating a prediction block that includes predicted pixels. The first neighboring pixels are peripheral to the block along a first edge of the block. The second pixels are generated using third neighboring pixels that are peripheral to a third edge of the block. The third edge is different from the first edge and the second edge. Generating the prediction block includes interpolating, using a first interpolation, the first neighboring pixels and the second pixels to obtain the predicted pixels.

    Adaptive stochastic entropy coding
    78.
    发明授权

    公开(公告)号:US10284854B2

    公开(公告)日:2019-05-07

    申请号:US15705751

    申请日:2017-09-15

    Applicant: Google LLC

    Abstract: Adaptive stochastic entropy encoding may include identifying a current portion of an input video stream, and identifying a current probability distribution, which may be an adapted probability distribution associated with a previously encoded portion of the video stream. Adaptive stochastic entropy encoding may include identifying a forward update probability distribution based on the current portion, generating a modified probability distribution for the current portion based on the forward update probability distribution and the current probability distribution, generating an encoded portion based on the current portion and the modified probability distribution, and generating an adapted probability distribution based on the current probability distribution and the forward update probability distribution.

    Ranked Reference Framework For Video Coding

    公开(公告)号:US20250047833A1

    公开(公告)日:2025-02-06

    申请号:US18717407

    申请日:2022-12-07

    Applicant: Google LLC

    Abstract: A new reference framework is described that ranks reference frames based on a normative procedure (e.g., a calculated score) and signals the reference frames based on their ranks. The bitstream syntax is simplified by using a context tree that relies on the ranking. Moreover, mapping reference frames to buffers does not have to be signaled and can be determined at the decoder. In an example, the identifier of a reference frame used to code a current block can include identifying a syntax element corresponding to the identifier, determining context information for the syntax element, determining a node of a context tree that includes the syntax element, and coding the syntax element according to a probability model using the context information associated with the node. The context tree is a binary tree that includes, as nodes, the available reference frames arranged in the ranking.

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