一种基于类haar小波的MCTF视频编码方案

在传统的基于运动补偿的时间滤波小波视频编码方案中,帧组尺寸和低通帧位置都是固定的,没有考虑到视频序列中运动的性质.本文提出了一种类似haar小波的基于运动补偿的时间滤波编码方案,利用互信息技术,根据视频的运动特征自适应的选择帧组尺寸和低通帧位置.同时,根据选定的帧组尺寸和低通帧位置决定时间上的编码层次.大量的实验比较了提出的方法和传统方法的压缩性能.当视频序列运动较为剧烈时,本文提出的自适应选择低通帧方法较固定低通帧方法的PSNR提高约0.3~0.5dB;当视频序列中运动缓急不一,如频繁的画面切换,本文提出的自适应的选择帧组尺寸的方法能取得更好的效果.     

Key-frame reference selection for non-feedback video communication

This article addresses the problem of reference picture optimization in video communication over error prone networks. A novel estimation model for transmission distortion is proposed. This model is capable of recursively estimating the overall end-to-end distortion caused by quantization, error propagation, and error concealment. Simulation results show that this model can accurately estimate channel distortion. Then, based on the distortion estimation model, a new non-feedback key-frame reference picture selection (KRPS) algorithm is developed. The optimum reference picture minimizes the transmission distortion under the rate-distortion optimization framework. Extensive experiment results demonstrate that the proposed KRPS algorithm substantially achieves more peak signal to noise ratio (PSNR) gain over traditional prediction, especially in low bit-rate transmission.