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Journal of Electronic Imaging

Coded image quality assessment based on a new contrast masking model
Author(s): Nachida Bekkat; Abdelhakim Saadane
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Paper Abstract

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.

Paper Details

Date Published: 1 April 2004
PDF: 8 pages
J. Electron. Imaging. 13(2) doi: 10.1117/1.1666872
Published in: Journal of Electronic Imaging Volume 13, Issue 2
Show Author Affiliations
Nachida Bekkat, Univ. de Nantes (France)
Abdelhakim Saadane, Univ. de Nantes (France)


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