An Improved Inter-Frame Prediction Algorithm for Video Coding Based on Fractal and H.264 - Shiping Zhu; Shupei Zhang; Chenhao Ran (IEEE Access, 2017)
Video compression has become more and more important nowadays along with the increasing application of video sequences and rapidly growing resolution of them. H.264 is a widely applied video coding standard for academic and commercial purposes. And fractal theory is one of the most active branches in modern mathematics, which has shown a great potential in compression. In this paper, this study proposes an improved inter prediction algorithm for video coding based on fractal theory and H.264. This study take the same approach to make intra predictions as H.264 and this study adopt the fractal theory to make inter predictions. Some improvements are introduced in this algorithm. First, luminance and chrominance components are coded separately and the partitions are no longer associated as in H.264. Second, the partition mode for chrominance components has been changed and the block size now rages from 16 × 16 to 4 × 4, which is the same as luminance components. Third, this study introduced adaptive quantization parameter offset, changing the offset for every frame in the quantization process to acquire better reconstructed image. Comparison between the improved algorithm, the original fractal compress algorithm and JM19.0 (The latest H.264/AVC reference software) confirms a slightly increase in Peak Signal-to-Noise Ratio, a significant decrease in bitrate while the time consumed for compression remains less than 60% of that using JM19.0.