1 April 2004 Coded image quality assessment based on a new contrast masking model
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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) Society of Photo-Optical Instrumentation Engineers (SPIE)
Nachida Bekkat, Nachida Bekkat, Abdelhakim Saadane, Abdelhakim Saadane, } "Coded image quality assessment based on a new contrast masking model," Journal of Electronic Imaging 13(2), (1 April 2004). https://doi.org/10.1117/1.1666872 . Submission:

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