A comprehensive analysis of adaptive image restoration techniques in the presence of different noise models

Abstract

Any deprivation caused in the image signal can be thought as a noise. When any image signal is routed through wireless or wired medium it experiences deterioration because of channel characteristics. By knowing the type of noise interfered in the signal, we can use the pertinent filtering techniques to remove the noise from the image. Restoration of the image signal corrupted by noise is very essential for better communication. This paper provides the digital image handling techniques in MATLAB to restore the corrupted image. In this paper, different filtering methods have been discussed in the presence of two separate noise models that distort images. Four different  techniques of filtering, ‘Mean/Average filtering', 'Median filtering', 'Adaptive median filtering' and 'Image Averaging' have been chosen against selected noise models. At the end of the paper we will compare which filtering technique works best for removing a particular noise.