Linear and nonlinear image restoration under the presence of mixed noise

The restoration of images in the presence of mixed noise is considered. An approach that exploits space-varying objective functions, which results in locally varying filtering schemes for the restoration problem, is introduced. The analysis is performed for both linear and nonlinear image-formation systems. It is found that the approach results in a degradation of the detailed structure existing in the original image. Hence, the problem of simultaneous noise removal and edge preservation in image restoration is addressed. The ultimate objective is to invert the linear and nonlinear transformations introduced by the image-formation system and remove as much long- as well as short- and/or medium-tailed noise, while simultaneously preserving the detailed structure of the image. The properties of the proposed algorithms are demonstrated through restoration examples