ENTROPY CODING FOR NEURAL-BASED MEDIA COMPRESSION

    公开(公告)号:US20230262267A1

    公开(公告)日:2023-08-17

    申请号:US17650728

    申请日:2022-02-11

    CPC classification number: H04N19/91 H04N19/124 G06T9/002 G06N3/0472

    Abstract: This disclosure describes entropy coding techniques for media data coded using neural-based techniques. A media coder is configured to determine a probability distribution function parameter for a data element of a data stream coded by a neural-based media compression technique, wherein the probability distribution function parameter is a logarithmic function of a standard deviation of a probability distribution function of the data stream, determine a code vector based on the probability distribution function parameter, and entropy code the data element using the code vector.

    Extended multiple transform selection for video coding

    公开(公告)号:US11240534B2

    公开(公告)日:2022-02-01

    申请号:US16838553

    申请日:2020-04-02

    Abstract: An example device for coding video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: code a first codeword representing a selected transform scheme of a set of transform candidates of a multiple transform selection (MTS) scheme for a current block of video data, the selected transform scheme being a secondary transform of a set of available secondary transforms to be applied in addition to a primary transform; code a second codeword representing the secondary transform from the set of available secondary transforms; and apply the primary transform and the secondary transform during coding of residual data for the current block. The second codeword may be a value for a low-frequency non-separable transform (LFNST) syntax element.

    EXTENDED MULTIPLE TRANSFORM SELECTION FOR VIDEO CODING

    公开(公告)号:US20220030278A1

    公开(公告)日:2022-01-27

    申请号:US17450509

    申请日:2021-10-11

    Abstract: An example device for coding video data includes a memory configured to store video data; and one or more processors implemented in circuitry and configured to: code a first codeword representing a selected transform scheme of a set of transform candidates of a multiple transform selection (MTS) scheme for a current block of video data, the selected transform scheme being a secondary transform of a set of available secondary transforms to be applied in addition to a primary transform; code a second codeword representing the secondary transform from the set of available secondary transforms; and apply the primary transform and the secondary transform during coding of residual data for the current block. The second codeword may be a value for a low-frequency non-separable transform (LFNST) syntax element.

    PARALLELIZED RATE-DISTORTION OPTIMIZED QUANTIZATION USING DEEP LEARNING

    公开(公告)号:US20210329267A1

    公开(公告)日:2021-10-21

    申请号:US17070589

    申请日:2020-10-14

    Abstract: A video encoder determines scaled transform coefficients, wherein determining the scaled transform coefficients comprises scaling transform coefficients of a block of the video data according to a given quantization step. The video encoder determines scalar quantized coefficients, wherein determining the scalar quantized coefficients comprises applying scalar quantization to the scaled transform coefficients of the block. Additionally, the video encoder applies a neural network that determines a respective set of probabilities for each respective transform coefficient of the block. The respective set of probabilities for the respective transform coefficient includes a respective probability value for each possible adjustment value in a plurality of possible adjustment values. Inputs to the neural network include the scaled transform coefficients and the scalar quantized coefficients. The video encoder determines, based on the set of probabilities for a particular transform coefficient of the block, a quantization level for the particular transform coefficient.

    TRANSFORM UNIT DESIGN FOR VIDEO CODING

    公开(公告)号:US20210092381A1

    公开(公告)日:2021-03-25

    申请号:US17025529

    申请日:2020-09-18

    Abstract: An example device for decoding video data includes a memory configured to store the video data and one or more processors coupled to the memory. The one or more processors are configured to reorganize 2-D dequantized coefficients according to a first ordering. The one or more processors are configured to apply an inverse low-frequency non-separable transform (LFNST) to the reorganized 2-D dequantized coefficients to create inverse transformed coefficients. The one or more processors are configured to reorganize the inverse transformed coefficients according to a second ordering, the second ordering being based on an array including values, wherein each value in the array corresponds to a position in a 2-D block and the values in the array denote indices of the 2-D block in a defined order. The one or more processors are configured to decode the video data based on the second ordered inverse transformed coefficients.

Patent Agency Ranking