Image Quality Assessment Based on Improved Feature Similarity Metric
In this paper, a new full-reference metric for image quality assessment is proposed, which is based on the recent feature similarity (FSIM) index and incorporates proper human visual system (HVS) characteristics. This method improves FSIM by using the CSF (Contrast Sensitivity Function) operator and the contrast masking operator in DCT domain. To test the performance of the proposed metric, we have carried out experiments on LIVE database. Experimental results demonstrate that the improved metric can achieve higher consistency with the subjective evaluation than FSIM and other relevant state-of-the-art image quality assessment metrics.
Zhengyou Wang Zhenxing Li Weisi Lin Chenchen Liu
Shijiazhuang Tiedao University, Shijiazhuang Jiangxi University of Finance & Economics, Nanchang Jiangxi University of Finance & Economics, Nanchang Nanyang Technological University, 50 Nanyang Avenue, Singapore Shijiazhuang Tiedao University, Shijiazhuang
国际会议
2011亚太信号与信息处理协会年度峰会(APSIPAASC 2011)
西安
英文
1-5
2011-10-18（万方平台首次上网日期，不代表论文的发表时间）