用于视频压缩的变换（DCT）视频编码残差的预测
Prediction of Transformed (DCT) Video Coding Residual for Video Compression
摘要：
视频压缩已经借助于分析-合成，并且更具体地借助于修复来研究。我们方法的第一部分是开发图像中DCT系数的修复。这显示了良好的效果，图像压缩没有超越今天的压缩标准，如JPEG。然后，我们研究了在视频编码器中集成相同的方法，特别是在广泛使用的H264 AVC标准编码器中，但是相同的方法可以在HEVC的框架中使用。这项工作的独创性在于取消在编码器，然后自动恢复，在解码器，一些精心挑选的DCT残差系数。为此，我们已经开发了一个恢复模型的转换系数。通过使用基于总变分的模型，我们推导出被抑制或改变的变换系数的重建条件。这里的主要目的，在视频编码的上下文中，是提高现有的编码器的率失真性能。为此，基于图像正则化过程，DCT恢复被用作变换系数的空间预测的附加预测步骤。该方法已成功地测试与H.264 AVC视频编解码器标准。
英文摘要：
Video compression has been investigated by means of analysis-synthesis, and more particularly by means of inpainting. The first part of our approach has been to develop the inpainting of DCT coefficients in an image. This has shown good results for image compression without overpassing todays compression standards like JPEG. We then looked at integrating the same approach in a video coder, and in particular in the widely used H264 AVC standard coder, but the same approach can be used in the framework of HEVC. The originality of this work consists in cancelling at the coder, then automatically restoring, at the decoder, some well chosen DCT residual coefficients. For this purpose, we have developed a restoration model of transformed coefficients. By using a total variation based model, we derive conditions for the reconstruction of transformed coefficients that have been suppressed or altered. The main purpose here, in a video coding context, is to improve the ratedistortion performance of existing coders. To this end DCT restoration is used as an additional prediction step to the spatial prediction of the transformed coefficients, based on an image regularization process. The method has been successfully tested with the H.264 AVC video codec standard.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
