Probability mapping for entropy coding

    公开(公告)号:US11178409B2

    公开(公告)日:2021-11-16

    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.

    REFINED ENTROPY CODING FOR LEVEL MAPS
    3.
    发明申请

    公开(公告)号:US20200053367A1

    公开(公告)日:2020-02-13

    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
    4.
    发明申请

    公开(公告)号:US20200021820A1

    公开(公告)日:2020-01-16

    申请号:US16580226

    申请日:2019-09-24

    Applicant: GOOGLE LLC

    Abstract: A method for coding a current block using an intra-prediction mode includes defining a mapping from available intra-prediction modes to intra-prediction classes; determining, using the mapping, a first intra-prediction class of a first intra-prediction mode used for decoding a first neighboring block of the current block; determining, using the mapping, a second intra-prediction class of a second intra-prediction mode used for decoding a second neighboring block of the current block; using the first intra-prediction class and the second intra-prediction class as indices into a list of available context models to select a context model for coding the intra-prediction mode; and coding the intra-prediction mode using the context model. A first number of the intra-prediction classes is smaller than a second number of the available intra-prediction modes. each class is an ordinal value, and each available intra-prediction mode uniquely maps to one class of the intra-prediction classes.

    Regularization Of A Probability Model For Entropy Coding

    公开(公告)号:US20250150641A1

    公开(公告)日:2025-05-08

    申请号:US18836986

    申请日:2022-12-29

    Applicant: GOOGLE LLC

    Abstract: Entropy coding a sequence of syntax elements is described where an observation for a syntax element of the sequence is determined, and the observation is arithmetic coded using the probability model. Thereafter, the probability model is updated using a time-variant update rate to produce an updated probability model. Updating the probability model includes regularizing one or more probability values of the probability model so no probability of the updated probability model is below a defined minimum resolution. As a result, the use of a minimum probability value during the arithmetic coding, which can distort probability model, may be omitted.

    Directional intra-prediction coding

    公开(公告)号:US10992939B2

    公开(公告)日:2021-04-27

    申请号:US15790516

    申请日:2017-10-23

    Applicant: GOOGLE LLC

    Inventor: Joseph Young

    Abstract: Coding a current block using a directional intra-prediction mode is described. A filter to apply to reference pixels peripheral to the current block is determined using a prediction angle of the intra-prediction mode and a size of the current block. The reference pixels are filtered using the filter to generate modified reference pixels, and a prediction block is generated for the current block using the intra-prediction mode and the modified reference pixels.

    INTRA-PREDICTION EDGE FILTERING
    7.
    发明申请

    公开(公告)号:US20190174143A1

    公开(公告)日:2019-06-06

    申请号:US16267552

    申请日:2019-02-05

    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. An apparatus determines, using the prediction angle, a filter to apply to the pixels peripheral to the current block; filters, using the filter, at least some of the pixels peripheral to the current block resulting in modified pixels; and generates a prediction block for the current block using the intra prediction mode and the modified pixels.

    DIRECTIONAL INTRA-PREDICTION CODING
    8.
    发明申请

    公开(公告)号:US20190124339A1

    公开(公告)日:2019-04-25

    申请号:US15790516

    申请日:2017-10-23

    Applicant: GOOGLE LLC

    Inventor: Joseph Young

    Abstract: Coding a current block using a directional intra-prediction mode is described. A filter to apply to reference pixels peripheral to the current block is determined using the a prediction angle of the intra-prediction mode and a size of the current block. The reference pixels are filtered using the filter to generate modified reference pixels, and a prediction block is generated for the current block using the intra-prediction mode and the modified reference pixels.

    Using rate distortion cost as a loss function for deep learning

    公开(公告)号:US11956447B2

    公开(公告)日:2024-04-09

    申请号:US17601639

    申请日:2019-03-21

    Applicant: Google LLC

    CPC classification number: H04N19/147 G06T9/002 H04N19/176 H04N19/96

    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.

    Context modeling for intra-prediction modes

    公开(公告)号:US10834410B2

    公开(公告)日:2020-11-10

    申请号:US16580226

    申请日:2019-09-24

    Applicant: GOOGLE LLC

    Abstract: A method for coding a current block using an intra-prediction mode includes defining a mapping from available intra-prediction modes to intra-prediction classes; determining, using the mapping, a first intra-prediction class of a first intra-prediction mode used for decoding a first neighboring block of the current block; determining, using the mapping, a second intra-prediction class of a second intra-prediction mode used for decoding a second neighboring block of the current block; using the first intra-prediction class and the second intra-prediction class as indices into a list of available context models to select a context model for coding the intra-prediction mode; and coding the intra-prediction mode using the context model. A first number of the intra-prediction classes is smaller than a second number of the available intra-prediction modes. each class is an ordinal value, and each available intra-prediction mode uniquely maps to one class of the intra-prediction classes.

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