Blind evaluation of additive noise variance in textured images by nonlinear processing of block DCT coefficients

Abstract

The problem of blind evaluation of noise variance in images is considered. Typical approaches commonly presume getting a set of variance estimations in small size blocks and further analysis of the obtained estimations set distribution with finding its maximum. However, such methods suffer from the common drawback that their accuracy becomes drastically worse if an image contains a lot of texture. To alleviate this drawback we propose an approach based on the fact that the statistical properties of DCT coefficients corresponding to high spatial frequencies in small size blocks greatly depend upon noise variance. As shown, these coefficients can be processed in nonlinear manner in order to eliminate the influence of informative component of the image itself. The dependence of the method accuracy on the used nonlinear operation and its parameters is carried out. It is shown that the proposed method produces appropriately good accuracy of blind evaluation of noise variance for a set of considered test images. The comparison analysis of the proposed method and some known analogs is performed.