Image visual quality restoration by cancellation of the unmasked noise

The aim of image restoration is to find an estimate of the ideal image using a priori information about blur and/or noise and/or the ideal image. Classical criterion are minimum least square, minimum mean square error or maximum a posteriori probability. The choice of the criterion used to measure the estimation quality is crucial for the design of the restoration algorithm. The authors propose a new criterion based on a visual model: it is based on perceptual masking. Thereafter, they propose a new restoration algorithm dealing only with additive noise. The perceptual components of the image to restore which are corrupted by an additive noise above a visibility threshold are simply set to zero. Some results obtained for the post-processing of JPEG images are presented