Efficient noise reduction coding
    11.
    发明授权

    公开(公告)号:US10652552B1

    公开(公告)日:2020-05-12

    申请号:US16264814

    申请日:2019-02-01

    Applicant: GOOGLE LLC

    Abstract: Efficient noise reduction coding may include generating, by a processor, an encoded frame by encoding an input video frame. Encoding the input frame includes determining an estimated noise level for the input video frame, determining a minimum quantization parameter level based on the estimated noise level for the input video frame, determining a quantization parameter value for encoding the input frame such that the quantization parameter value is at least the minimum quantization parameter level, obtaining the encoded frame by encoding the input frame in accordance with the quantization parameter level, including the encoded frame in an output bitstream, and outputting the output bitstream.

    CONTEXT MODELING FOR INTRA-PREDICTION MODES
    12.
    发明申请

    公开(公告)号:US20190124340A1

    公开(公告)日:2019-04-25

    申请号:US15819651

    申请日:2017-11-21

    Applicant: GOOGLE LLC

    Abstract: A method for intra-coding a current block using an intra-prediction mode includes determining a left intra-mode of a left neighbor block and determining an above intra-mode of an above neighbor block. The method also includes, on condition that the left intra-mode and the above intra-mode are a same mode, using that same mode to determine a probability distribution for coding the intra-prediction mode and, on condition that at least one of the left intra-mode or the above intra-mode is a smooth intra-prediction mode, using the other of the left intra-mode and the above intra-mode to determine the probability distribution for coding the intra-prediction mode. The method also includes coding the intra-prediction mode using the probability distribution.

    Intra-prediction edge filtering
    13.
    发明授权

    公开(公告)号:US10225578B2

    公开(公告)日:2019-03-05

    申请号:US15590274

    申请日:2017-05-09

    Applicant: GOOGLE LLC

    Inventor: Joseph Young

    Abstract: Coding a current block using a directional intra prediction mode is disclosed. The intra prediction mode includes a prediction angle and uses pixels peripheral to the current block to generate a prediction block. A method includes determining, using the prediction angle, a filter to apply to the pixels peripheral to the current block, filtering, using the filter, at least some of the pixels peripheral to the current block resulting in modified pixels, and generating a prediction block for the current block using the intra prediction mode and the modified pixels.

    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.

    Refined entropy coding for level maps

    公开(公告)号:US10893280B2

    公开(公告)日:2021-01-12

    申请号:US16659666

    申请日:2019-10-22

    Applicant: GOOGLE LLC

    Abstract: An apparatus includes a memory and a processor. The processor is configured to execute instructions stored in the memory to obtain a transform type for decoding a transform block for the current block; select, based on the transform type, a template for coding a value of a non-zero map; select, based on the template, a context for entropy decoding the value of the non-zero map; and decode the value of the non-zero map based on the context. The non-zero map indicates which coefficients of the transform block have non-zero values. A method includes obtaining a transform class for coding a transform block for the current block, wherein the transform class corresponding to a transform type and a direction; selecting, based on the transform class, a coding context for coding a value of a non-zero map; and coding the value of the non-zero map based on the coding context.

    Context modeling for intra-prediction modes

    公开(公告)号:US10440369B2

    公开(公告)日:2019-10-08

    申请号:US15819651

    申请日:2017-11-21

    Applicant: GOOGLE LLC

    Abstract: A method for intra-coding a current block using an intra-prediction mode includes determining a left intra-mode of a left neighbor block and determining an above intra-mode of an above neighbor block. The method also includes, on condition that the left intra-mode and the above intra-mode are a same mode, using that same mode to determine a probability distribution for coding the intra-prediction mode and, on condition that at least one of the left intra-mode or the above intra-mode is a smooth intra-prediction mode, using the other of the left intra-mode and the above intra-mode to determine the probability distribution for coding the intra-prediction mode. The method also includes coding the intra-prediction mode using the probability distribution.

    REFINED ENTROPY CODING FOR LEVEL MAPS
    17.
    发明申请

    公开(公告)号:US20190124342A1

    公开(公告)日:2019-04-25

    申请号:US15798495

    申请日:2017-10-31

    Applicant: GOOGLE LLC

    Abstract: Coding using level maps is disclosed. A method includes coding a scan position, in a forward scan direction, corresponding to an end-of-block and coding, in a backward scan direction, a non-zero map indicating positions of the transform block containing non-zero transform coefficients. The method also includes coding, in the backward scan direction, lower-range level maps, each lower-range level map having a respective map level up to a maximum map level, the lower-range level map indicating which absolute values of the non-zero transform coefficients are equal to the respective map level and which absolute values of the non-zero transform coefficients are greater than the respective map level. The method also includes coding a coefficient residual map, each residual coefficient of the coefficient residual map corresponding to a respective non-zero transform coefficient of the transform block having an absolute value exceeding the maximum map level.

    Using Rate Distortion Cost as a Loss Function for Deep Learning

    公开(公告)号:US20220201316A1

    公开(公告)日:2022-06-23

    申请号:US17601639

    申请日:2019-03-21

    Applicant: Google LLC

    Abstract: An apparatus for encoding an image block includes a processor that presents, to a machine-learning model, the image block, obtains the partition decision for encoding the image block from the model, and encodes the image block using the partition decision. The model is trained to output a partition decision for encoding the image block by using training data for a plurality of training blocks as input, the training data including for a training block, partition decisions for encoding the training block, and, for each partition decision, a rate-distortion value resulting from encoding the training block using the partition decision. The model is trained using a loss function combining a partition loss function based upon a relationship between the partition decisions and respective predicted partitions, and a rate-distortion cost loss function based upon a relationship between the rate-distortion values and respective predicted rate-distortion values.

    PROBABILITY MAPPING FOR ENTROPY CODING
    20.
    发明申请

    公开(公告)号:US20200213599A1

    公开(公告)日:2020-07-02

    申请号:US16812539

    申请日:2020-03-09

    Applicant: GOOGLE LLC

    Abstract: A method for coding a frame of a video stream includes selecting a first initial probability distribution for coding at least a first portion of the frame; updating, to obtain an updated first initial probability distribution and using backward adaptivity, the first initial probability distribution while coding the first portion of the frame; mapping the updated first initial probability distribution to a second initial probability distribution; and coding a second portion of the frame using the second initial probability distribution as an initial probability distribution. The first values of the first initial probability distribution are described using M bits, wherein M is a first positive integer. Second values of the updated first initial probability distribution are described using N bits, where N is a second positive integer that is greater than M. Third values of the second initial probability distribution are described using M bits.

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