摘要
进行客观视频质量评价时,为了与主观评价结果尽可能一致,需要考虑视频的动态特性和人眼观看的视觉特性,因此本文提出一种基于显著区域和运动特性加权的视频质量评价方法。该评价指标基于传统的结构相似性指数(Structural similarity index measurement,SSIM)方法并在此基础上作了改进。首先通过频谱分析得到空域显著度,通过视觉注意模型并结合运动特性获取时域显著度,并根据时、空显著度动态融合得到帧级显著度。以帧级显著度加权SSIM指数,便可得到整个视频帧的质量评价指标。在LIVE VQA标准数据集上的实验结果表明,该评价指标更加接近于人眼对视频质量的主观评价值。
To evaluate accurately the video quality and make it consistent with the subjective evaluation result,a video quality assessment method based on saliency region and motion characteristics weighting is proposed in this paper.This method is based on traditional structural similarity index measurement(SSIM)and makes some improvement.The spatial and temporal saliency is firstly extracted by spectrum analysis and visual attention model combined with motion characteristics,respectively.Then the frame saliency can be extracted by dynamic fusion of temporal and spatial saliency.Finally,the quality assessment index for entire video frame can be got by frame saliency weighted SSIM.The results of experiment on LIVE VQA standard data set show that this index is more close to objective assessment on video quality from human visual system.
出处
《数据采集与处理》
CSCD
北大核心
2017年第5期1061-1068,共8页
Journal of Data Acquisition and Processing
基金
深圳信息职业技术学院校级科研培育项目(QN201718)资助项目
深圳市科技计划项目(JCYJ20160608151239996)资助项目
关键词
人眼视觉系统
显著区域
时空显著度
运动特性
结构相似性指数
human visual system
region of saliency
spatio-temporal saliency
motion characteristics
structural similarity index