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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.
Highlights
With the development of Internet technology, image storage technology and image transmission technology have become the core content of multimedia [1]
In order to verify the overall effectiveness of the low frame rate video compression algorithm based on linear function model, it is necessary to test the low frame rate video compression algorithm based on linear function model
There are some problems in the image compression algorithm of power grid operation site, such as low compression definition, poor video image quality, and low compression efficiency
Summary
With the development of Internet technology, image storage technology and image transmission technology have become the core content of multimedia [1]. In [3], the combination of frame rate conversion technology and new video compression coding standard HEVC is conducive to improve the video compression efficiency. The proposed algorithm does not compensate the frame rate of the video image, resulting in low definition of the compressed video image. E adaptive compression of online video interframe signals can be realized by installing adaptive compression coding equipment, setting adaptive threshold, and inputting the motion estimation results and extracted video key frames into the encoder. (3) e 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
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