基于人类视觉系统的宏块级自适应频率加权算法

Macroblock-Level Adaptive Frequency Weighting Based on HVS

  • 摘要: 为提高视频编码主观质量,满足人类视觉特性,降低编码比特率,提出一种基于人类视觉系统的宏块级自适应频率加权算法。该算法利用人类视觉系统频率敏感性、视频图像内容特征和人眼对不同视频内容敏感度不同特性,定义了三种频率加权策略,并根据相邻宏块划分方式和预测模式为不同宏块选择不同的加权策略,实现了逐宏块更新量化矩阵。实验结果表明,本文算法在不引入更多计算复杂度的同时,较大程度提高了视频主观质量;与无频率加权算法相比,在相同主观质量下,降低约11%的编码比特数。

     

    Abstract: In order to improve the subjective quality of video coding, satisfy the properties of human visual, and reduce the bitrate of coding, a Macroblock-Level Adaptive Frequency Weighting Scheme is proposed in this paper. In the perceptual video coding scheme, the frequency sensitivity is one of the most important properties of HVS and is usually used to improve the subjective quality. In this paper, The spatial context, the side information and the properties of the human visual system are both taken into consideration. According to the effect of frequency weighting, three different strategies are defined, and the different areas in one picture can choose different frequency weighting strategies. Compared with the picture-level adaptive frequency weighting algorithms, the proposed algorithm can select different frequency weighting strategies and quantization matrices for each MB. The experimental results show that the proposed Macroblock-Level Adaptive Frequency Weighting algorithm (MBAFW) can improve the subjective quality significantly. Additionally, MBAFW algorithm can achieve about 11% bitrate reductions with almost the same subjective quality.

     

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