No-reference image quality assessment based on sparse representation
Author:
Funder
National Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
http://link.springer.com/content/pdf/10.1007/s00521-018-3497-y.pdf
Reference47 articles.
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2. Gu K, Zhai G, Lin W et al (2016) The analysis of image contrast: from quality assessment to automatic enhancement. IEEE Trans Cybern 46(1):284–297
3. Lin W, Jay Kuo CC (2011) Perceptual visual quality metrics: a survey. J Vis Commun Image Represent 22(4):297–312
4. Ma L, Deng C, Ngan KN et al (2013) Recent advances and challenges of visual signal quality assessment. China Commun 10(5):62–78
5. Wang Z, Bovik AC, Sheikh HR et al (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600–612
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