Image Coding, Decoding, and Quality Assessment

Coded image quality assessment based on a new contrast masking model

[+] Author Affiliations
Nachida Bekkat, Abdelhakim Saadane

Ecole Polytechnique de l’Universite´ de Nantes, IRCCyN/IVC, Rue Christian Pauc BP50609, 44306 Nantes, France E-mail: asaadane@ireste.fr

J. Electron. Imaging. 13(2), 341-348 (Apr 01, 2004). doi:10.1117/1.1666872
History: Received May 22, 2001; Revised Mar. 17, 2003; Revised May 27, 2003; Accepted Jul. 18, 2003; Online April 01, 2004
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The use of computational metrics to control and assess the visual quality of digital images is well known. This paper presents a quality metric including a visual channels representation and a new contrast masking model. Based on the measure of maximum quantization steps without visual impairments, the model considers both intrachannel and interchannel masking and is derived from extensive experiments conducted on noise and texture images instead of simple sinusoidal stimuli. The metric parameters are optimized in order to maximize the linear correlation coefficient as well as the Spearman rank-order correlation between the computed quality measures and the mean opinion score. © 2004 SPIE and IS&T.

© 2004 SPIE and IS&T

Citation

Nachida Bekkat and Abdelhakim Saadane
"Coded image quality assessment based on a new contrast masking model", J. Electron. Imaging. 13(2), 341-348 (Apr 01, 2004). ; http://dx.doi.org/10.1117/1.1666872


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