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• W3204131205 abstract "When using the current method to compress the low frame rate video animation video, there is no frame rate compensation for the video image, which cannot eliminate the artifacts generated in the compression process, resulting in low definition, poor quality, and low compression efficiency of the compressed low frame rate video animation video. In the context of new media, the linear function model is introduced to study the frame rate video animation video compression algorithm. In this paper, an adaptive detachable convolutional network is used to estimate the offset of low frame rate video animation using local convolution. According to the estimation results, the video frames are compensated to eliminate the artifacts of low frame rate video animation. After the frame rate compensation, the low frame rate video animation video is divided into blocks, the CS value of the image block is measured, the linear estimation of the image block is carried out by using the linear function model, and the compression of the low frame rate video animation video is completed according to the best linear estimation result. The experimental results show that the low frame rate video and animation video compressed by the proposed algorithm have high definition, high compression quality under different compression ratios, and high compression efficiency under different compression ratios." @default.
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• W3204131205 date "2021-09-27" @default.
• W3204131205 modified "2023-09-27" @default.
• W3204131205 title "Research on Low Frame Rate Video Compression Algorithm in the Context of New Media" @default.
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• W3204131205 doi "https://doi.org/10.1155/2021/7494750" @default.
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