Image Quality Assessment Based on SIFT and SSIM

摘要：

　　Image qua lity assessment (IQA) aims t o provide computational models to measure the image quality consistently with subjective assessments. The SSIM index brings IQA from pixel-based to structure-based stage. In this paper, a new similarity index based on SIFT features (SIFT-SSIM) for full reference IQA is presented. In the algorithm, proportion of matched features in extracted features of reference image and structural similarity are combined into a comprehensive quality index. Experiments on LIVE database demonstrate that SIFT-SSIM is competitive with most of state-of-the-art FR-IQA metrics, and it can achieve higher consistency with the subjective assessments in some distortion types.

关键词： Image Quality Assessment Full Reference Structural Similarity Space Invariant Feature Transform

作者: Weniun Lu Congli Li Yongchang Shi Xiaoning Sun

作者单位: New Star Research Institute of Applied Technology, Hefei 230031, China

会议类型: 国际会议

会议名称: 9th Conference on Image and Graphics Technologies and Applications(IGTA2014)(第九届图像图形技术与应用学术会议)

会议地点: 北京

会议语种:英文

页码: 2-8

在线出版日期: 2014-06-01（万方平台首次上网日期，不代表论文的发表时间）