基于3D混合树和视觉特性的视频可分级编码算法

分析了视频数据的3D小波系数分布特性,提出了一种基于混合3D树型结构和HVS特性的视频可分级编码算法.首先,依据小波低、高频系数的自相关性,确定相应的树型结构来扫描和处理时间维上的低、高频系数,明显减少了用于定位重要系数的同步信息;其次,依据人类视觉系统对各频率子带敏感程度的不同,对各子带系数进行加权,使得重构视频的重要系数得以排在码流前端,从而在很大程度上提高了中低码率下视频的重构质量.对多种标准测试视频的仿真实验验证了本文算法的有效性,与非对称树型结构编码方案和单一时空方向树结构方案相比,该算法解码图像的Y、U和V 3个分量的均峰值信噪比分别高出0.65dB、1.75dB、1.77dB和0.23dB、2.11dB、1.72dB.此外,算法有效抑制了振铃效应,并获得了更好的主观效果.

Scalable video coding algorithm based on 3D hybrid tree and visual characteristics

The distribution characteristic of three-dimensional wavelet coefficients of video data was ana ed,and a scalable video coding algorithm was subsequently addressed based on hybrid three-dimensional tree and human visual system (HVS) characteristics.First,the hybrid tree structure was adaptively determined according to the auto-correlation of low-pass and high-pass coefficients.It reduced obviously the number of ion bits locating significant wavelet coefficients when scanning and processing low-pass and high-pass coefficients in temporal dimension.Second,each wavelet coefficient was weighted in terms of HVS sensitivity to its corresponding subband.Significant coefficients thus tended to be coded with high priority and arranged at the front of bitstream,and the reconstructed video quality was improved at low and medium bitrates to a great extent.Experimental results in terms of peak signal-to-noise ratio (PSNR) verified the effectiveness of the proposed algorithm on several test videos with varying characteristics.0.65dB,1.75dB,and 1.77dB higher PSNR are gained than asymmetric 3-D orientation tree for Y,U,and V components,respectively.Moreover,0.23dB,2.11dB,and 1.72dB higher PSNR are reached than single temporal-spatial orientation tree separately for Y,U,and V components.Besides,better subjective quality is obtained through effectively attenuating ringing artifact.