[1]骞森,朱剑英.基于奇异值分解的图像质量评价[J].东南大学学报(自然科学版),2006,36(4):643-646.[doi:10.3969/j.issn.1001-0505.2006.04.032] 　Qian Sen,Zhu Jianying.Image quality measure using singular value decomposition[J].Journal of Southeast University (Natural Science Edition),2006,36(4):643-646.[doi:10.3969/j.issn.1001-0505.2006.04.032] 点击复制 基于奇异值分解的图像质量评价() 分享到： var jiathis_config = { data_track_clickback: true };

36

2006年第4期

643-646

2006-07-20

文章信息/Info

Title:
Image quality measure using singular value decomposition

Author(s):
Mechanical and Electronical Engineering Institute, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China

Keywords:

TP391.41
DOI:
10.3969/j.issn.1001-0505.2006.04.032

Abstract:
The limitations of several classic image quality measure algorithms based on error of gray-scale are analyzed, and the definition of image quality measure is extended, according to which the size of the original image can be different from that of the distorted image. The image matrix is transformed into vector by singular value decomposition. The angle between singular vectors of the original image and the distorted image is used to measure the image quality. The experimental results show that the algorithm proposed has good properties to image compression, noise and geometry distortion including scale, translation and rotation transform, and can be applied to the image quality measure definition proposed in this paper. The results are analyzed and compared with the measurement of human visual system.

参考文献/References:

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