Reduced-Reference Quality Assessment of Computer-Generated Images based on RVM.

被引:0
|
作者
Constantin, Joseph [1 ]
Delepoulle, Samuel [2 ]
Bigand, Andre [2 ]
Renaud, Christophe [2 ]
机构
[1] UL, Fac Sci 2, Lab Phys Appl, Dpt Math Appl,PR2N, BP 90656, Fanar, Jdeidet, Lebanon
[2] LISIC, ULCO, F-62228 Calais, France
关键词
Computer graphics; computer-generated images; Reduced-reference image quality metric; Relevance vector machine; Supervised learning;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reduced-reference image quality assessment needs no prior knowledge of reference image but only a minimal knowledge about processed images. A new reduced-reference image quality measure, based on Relevance Vector Machine (RVM), using a supervised learning framework and synthetic images is proposed. This new metric is compared with experimental psycho-visual data. A recently performed psycho-visual experiment provides psycho-visual scores on some synthetic images, and comprehensive testing demonstrates the good consistency between these scores and the quality measures we obtain. The proposed measure has been too compared with close methods like RBF, MLP and SVM and gives satisfactory performance.
引用
收藏
页码:320 / 324
页数:5
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