改进的基于AVS2的样点自适应补偿滤波算法

Improved algorithm for sample adaptive offset filter based on AVS2

样点自适应补偿(SAO)是第二代数字音视频编解码标准(AVS2)和高效视频编码(HEVC)标准中环路滤波耗时较多的一部分。针对现有自适应样点补偿算法计算量大、复杂度高等问题,提出一种改进的快速率失真算法。该算法主要通过分析各个边缘模式下不同补偿值的变化与所对应的率失真变化之间的关系,对原本定义的补偿值与写入码流的二元符号串之间的关系表进行修改,在不需要计算每个补偿值的率失真代价的情况下,设定一个提前终止条件,快速找到当前样值偏移补偿单元最优的补偿值。实验结果表明,与AVS2下的计算结果相比,在保证图像率失真基本不变的前提下,改进的算法减少了寻找最优补偿值的计算量以及75%的循环次数和33%的环路滤波运行时间,从而降低了计算的复杂度。

Sample Adaptive Offset（ SAO） is a time-consuming part of in-loop filter in the second generation of Audio Video coding Standard（ AVS2） and High Efficiency Video Coding（ HEVC） standard. Aiming at the problem that existing SAO algorithms had large amounts of computation and high complexity,an improved fast rate-distortion algorithm was proposed. In this new method,the original defined table of the offset values and its binary bit string to be written into the code stream were modified by analyzing the relationship between the different offset values of each class in the edge mode and its change of the rate-distortion,so that an early termination condition was set to quickly find the best offset value for the current SAO unit without calculating the rate-distortion cost of each offset. The experimental results show that,compared with the calculation results in AVS2,the proposed algorithm reduces not only the calculation amounts but also the number of cycles by75% to find the best offset values and the operating time of in-loop filter by 33%,which effectively lowers the complexity of the calculation in ensuring the rate-distortion of image barely changed.