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.

    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.

    COMPOUND PREDICTION FOR VIDEO CODING
    5.
    发明公开

    公开(公告)号:US20240333961A1

    公开(公告)日:2024-10-03

    申请号:US18742180

    申请日:2024-06-13

    Applicant: GOOGLE LLC

    Abstract: Generating a compound predictor block includes generating a first predictor block and generating a second predictor block. The first predictor block includes a first pixel and the second predictor block includes a second pixel. The first and the second pixels are located at a same location within the first predictor block and the second predictor block, respectively. A first weight is determined for the first pixel based on a difference between a first value of the first pixel and a second value of the second pixel. A second weight is determined for the second pixel based on 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 based on a weighted sum of the first pixel and the second pixel based on the first weight and the second weight.

    Video Coding With Guided Machine Learning Restoration

    公开(公告)号:US20240098280A1

    公开(公告)日:2024-03-21

    申请号:US18272862

    申请日:2021-01-19

    Applicant: Google LLC

    CPC classification number: H04N19/176 H04N19/30

    Abstract: Image coding using guided machine learning restoration may include obtaining reconstructed frame data by decoding, obtaining a restored frame by restoring the reconstructed frame, and outputting the restored frame. Obtaining the restored frame may include obtaining a reconstructed block, obtaining guide parameter values, obtaining a restored block, and including the restored block in the restored frame. Obtaining the restored block may include inputting the reconstructed block to an input layer of a trained guided convolutional neural network, wherein the neural network is constrained such that an output layer has a defined cardinality of channels, obtaining, from the output layer, neural network output channel predictions, obtaining a guided neural network prediction as a linear combination of the guide parameter values and the neural network output channel predictions, and generating the restored block using the guided neural network prediction.

    EXTENDED TRANSFORM PARTITIONS FOR VIDEO COMPRESSION

    公开(公告)号:US20210409705A1

    公开(公告)日:2021-12-30

    申请号:US16912767

    申请日:2020-06-26

    Applicant: GOOGLE LLC

    Abstract: Transform-level partitioning of a prediction residual block is performed to improve compression efficiency of video data. During encoding, a prediction residual block is generated responsive to prediction-level partitioning performed against a video block, a transform block partition type to use is determined based on the prediction residual block, a non-recursive transform-level partitioning is performed against the prediction residual block according to the transform block partition type, and transform blocks generated as a result of the transform-level partitioning are encoded to a bitstream. During decoding, a symbol representative of the transform block partition type used to encode transform blocks is derived from the bitstream, inverse transformed blocks are produced by inverse transforming encoded video data associated with the prediction residual block, and the prediction residual block is reproduced according to the transform block partition type and used to reconstruct the video block, which is output within an output video stream.

    Inter-Intra Prediction With Implicit Models
    10.
    发明公开

    公开(公告)号:US20230291925A1

    公开(公告)日:2023-09-14

    申请号:US18008209

    申请日:2020-07-01

    Applicant: Google LLC

    CPC classification number: H04N19/52 H04N19/176 H04N19/593 H04N19/105

    Abstract: Video coding in accordance with an inter-intra prediction model may include coding an inter-prediction motion vector for a current block of a current frame, obtaining spatial block-context pixels oriented relative to the current block, generating an inter-prediction block, generating a corresponding set of reference block-context pixels oriented relative to the inter-prediction block, identifying inter-intra prediction parameters that correspond with minimizing error between the spatial block-context pixels and the reference block-context pixels, generating a prediction block for the current block by, for a current pixel of the current block, obtaining an inter-prediction pixel, determining a predictor for the current pixel using a combination of the inter-prediction pixel and the inter-intra prediction parameters, and including the predictor in the prediction block.

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