VIDEO CODING METHOD ON BASIS OF SECONDARY TRANSFORM, AND DEVICE THEREFOR

    公开(公告)号:US20240348829A1

    公开(公告)日:2024-10-17

    申请号:US18742373

    申请日:2024-06-13

    CPC classification number: H04N19/61 H04N19/132 H04N19/159 H04N19/176 H04N19/18

    Abstract: A video transform method includes: receiving a quantized transform coefficient for a target block and a transform index for a non-separated secondary transform; inverse-quantizing the quantized transform coefficient; deriving an input transform coefficient size indicating the length of the inverse-quantized transform coefficient to which the non-separated secondary transform has been applied, an output transform coefficient size indicating the length of a modified transform coefficient to which the non-separated secondary transform has been applied, and a transform set mapped to the intra mode of the target block, when the transform index does not indicate that the non-separated secondary transform is not performed; and deriving the modified transform coefficient on the basis of a matrix operation on a transform kernel matrix in the transform set indicated by the transform index, and a transform coefficient list corresponding to the input transform coefficient size.

    METHOD AND DEVICE FOR DESIGNING LOW-FREQUENCY NON-SEPARABLE TRANSFORM

    公开(公告)号:US20240291992A1

    公开(公告)日:2024-08-29

    申请号:US18571605

    申请日:2022-06-16

    CPC classification number: H04N19/132 H04N19/105 H04N19/176 H04N19/18

    Abstract: An image decoding method according to this document comprises the steps of: deriving an LFNST matrix for a current block on the basis of an LFNST index derived from LFNST index information and an LFNST set index; deriving modified transform coefficients on the basis of transform coefficients and the LFNST matrix; and generating residual samples for the current block on the basis of the modified transform coefficients, wherein when the width or height of the current block has a value of 16 and both the width and height have a value of 16 or more, the LFNST matrix may be derived as a 96×32 dimensional matrix. Therefore, coding performance achievable by the LFNST can be maximized within the implementation complexity permitted in forthcoming standards.

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