Performance analys of segmentation-based method for blind evaluation of additive noise in images

There is a practical need in blind and automatic evaluation of noise characteristics in remote sensing images, especially multi and hyperspectral ones. It is both desirable to evaluate noise type and variance. This is needed for image filtering, classification, compression, edge detection and other operations of image processing. In the paper we address the task of noise variance evaluation supposing that noise type is known a priori or determined in advance. The main focus is on estimation of additive noise variance although the obtained results can be easily generalized to other types of noise (signal-dependent, multiplicative). There are quite many different methods for blind evaluation of additive noise variance. Two basic groups of methods are techniques operating in spatial and spectral domains. However, most methods of noise variance estimation in spectral domain that are rather accurate for i.i.d. noise case fail if noise is spatially correlated.