METHOD, APPARATUS, AND MEDIUM FOR VIDEO PROCESSING

    公开(公告)号:US20250039401A1

    公开(公告)日:2025-01-30

    申请号:US18913890

    申请日:2024-10-11

    Abstract: Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, for a conversion between a current video block of a video and a bitstream of the video, a distortion value of the current video block based on a set of distortion metrics, the set of distortion metrics comprising at least one of: a first distortion metric determined according to a first machine learning model, a second distortion metric determined according to a second machine learning model, or a third distortion metric determined without using the first and second machine learning models; and performing the conversion based on the distortion value. In this way, a rate-distortion optimization process based on the distortion value can be improved, and thus the coding performance can be enhanced.

    METHOD, APPARATUS, AND MEDIUM FOR VIDEO PROCESSING

    公开(公告)号:US20240244226A1

    公开(公告)日:2024-07-18

    申请号:US18622405

    申请日:2024-03-29

    CPC classification number: H04N19/147 H04N19/176 H04N19/42 H04N19/80 H04N19/132

    Abstract: Embodiments of the present disclosure provide a solution for video processing. A method for video processing is proposed. The method comprises: determining, during a conversion between a target video block of a video and a bitstream of the video, a distortion metric for the target video block based at least in part on at least one distortion of: a set of filtered distortions of the target video block according to a set of machine learning models, or a second distortion of the target video block determined without using the set of machine learning models; determining, based on the distortion metric, information regarding using the set of machine learning models in a rate-distortion optimization (RDO) process on the target video block; and performing the conversion based on the information. In this way, the RDO process can be improved, and thus the coding performance can be enhanced.

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