NEURAL NETWORK-BASED DEBLOCKING FILTERS
    71.
    发明公开

    公开(公告)号:US20230224505A1

    公开(公告)日:2023-07-13

    申请号:US18080201

    申请日:2022-12-13

    Abstract: A method and apparatus for reducing artifacts in a compressed image using a neural-network based deblocking filter. The method may include receiving at least one reconstructed image, wherein each reconstructed image comprises one or more reconstructed blocks and extracting boundary areas associated with boundaries of the one or more reconstructed blocks in the at least one reconstructed image. The extracted boundary areas may be input in a trained deblocking model to generate boundary areas having reduced artifacts and the trained deblocking mode is trained on training data based on estimated compression by a neural image compression (NIC) network. The edge areas associated with the generated boundary areas may be removed; and at least one reconstructed image with reduced artifacts may be generated based on the generated boundary areas.

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