吉林大学学报(工学版) ›› 2016, Vol. 46 ›› Issue (2): 639-645.doi: 10.13229/j.cnki.jdxbgxb201602045

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No-reference quality assessment based on the statistics in Cntourlet domain

JIAO Shu-hong1, QI Huan1, LIN Wei-si2, TANG Lin1, SHEN Wei-he3   

  1. 1.College of Information and Communication Engineering,Harbin Engineering University,Harbin 150001,China;
    2.School of Computer Engineering,Nanyang Technological University,Singapore 639798,Singapore;
    3.Science and Technology on Space Physics Laboratory,China Academy of Launch Vehicle Technology,Beijing 100076,China
  • Received:2014-08-28 Online:2016-02-20 Published:2016-02-20

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Abstract: The statistic features in Cntourlet domain are employed to build the natural statistic model and the tested image model first. Then a no-reference assessment algorithm in Contourlet domain (SCIQR) is proposed. Experiment results on subjective databases show that SCIQR outperforms the classical full-reference image quality assessment algorithm and the universal no-reference algorithm no-matter on single distortion type images and on the set of different types of distortion images. This demonstrates that SCIQR has good universality.

Key words: information processing technology, image quality assessment, statistics in Contourlet domain

CLC Number: 

  • TN911
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