基于非局部低秩和自适应量化约束先验的HEVC后处理算法

经高效视频编解码标准HEVC压缩后的视频在高压缩比、低码率的情况下存在明显的压缩效应。针对该问题,提出了一种基于非局部低秩(Non-local Low-rank,NLLR)和自适应量化约束(Adaptive Quantization Constraint,AQC)先验的HEVC后处理算法。该算法首先构造在最大后验概率框架下的优化问题,然后利用解码后的压缩视频和量化参数QP获取非局部低秩和自适应量化约束先验信息,最后利用split-Bregman迭代算法来解决所提的优化问题,从而有效去除压缩效应,提升重建视频质量。其中,非局部低秩先验通过构建基于相似块聚类的非局部低秩模型来获得;自适应量化约束先验通过联合不同量化参数QP下的约束特性与视频的DCT域块活动性来获得。实验结果表明,在同等码率的情况下,与HEVC标准相比,所提算法在帧内编码模式下可以达到平均0.2597 dB的PSNR提升,在帧间编码模式下可以达到平均0.2828 dB的PSNR提升。

HEVC Post-processing Algorithm Based on Non-local Low-rank and Adaptive Quantization Constraint Prior

Video compressed by HEVC has an obvious compression effect under the condition of a high compression ratio and a low bit rate.To solve this problem,a post-processing algorithm of HEVC based on non-local low-rank(NLLR)and adaptive quantization constraint(AQC)prior is proposed.This algorithm firstly constructs the optimization problem within the maximum priori probability framework.Then,the decoded compressed video and quantization parameters QP are used to obtain the NLLR and AQC prior information.Finally,the split-Bregman iterative algorithm is used to solve the optimization problem,so as to effectively remove the compression effect and improve the quality of reconstructed video.Among them,the NLLR prior is obtained by constructing the non-local low-rank model based on similar-block clustering.The AQC prior is obtained by combining the constraint characteristics under different quantization parameters QP and the DCT domain block activity of video.Experimental results show that the proposed algorithm can achieve an average PSNR improvement of 0.2597 dB in intra-frame coding mode and an average PSNR improvement of 0.2828 dB in inter-frame coding mode compared with HEVC standard at the same bit rate.