吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (4): 1337-1343.doi: 10.13229/j.cnki.jdxbgxb201604046

• Orginal Article • Previous Articles     Next Articles

No-reference blurring image quality assessment based on local standard deviation and saliency map

LU Yan-fei1, 2, 3, ZHANG Tao1, ZHENG Jian3, LI Ming1, 2, 3, ZHANG Cheng1, 2, 3   

  1. 1.Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences, Changchun 130033, China;
    2.University of Chinese Academy of Sciences, Beijing 100049, China;
    3.Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, China
  • Received:2015-02-04 Online:2016-07-20 Published:2016-07-20

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Abstract: In order to evaluate the quality of blur image effectively, a no-reference image quality assessment method based on local standard deviation and saliency map is proposed. First, the Gaussian low-pass filter is used to construct a reference image through blurring the given image. Then, two features, namely local standard deviation map and saliency map, are selected to evaluate the quality of the blur image according to the changes of the two features before and after the blurring process. The proposed method is tested on LIVE database and CSIQ database, on which the Pearson linear correlation coefficients are 0.9315 and 0.9254 respectively, and the Spearman rank correlation coefficients are 0.9258 and 0.8962 respectively. Experimental results indicate that the proposed method is close to the state-of-art method LPC-SI, however its computational complexity is much lower, only about 4.7% of that of LPC-SI.

Key words: information processing, blur image quality metric, reblur effect, local standard deviation, saliency map

CLC Number: 

  • TN911.73
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