A Review & Analysis of Image Filters for Impulse Noise - Kaur, Manmeet; Mangat, Kamaljeet Kaur (International Journal of Computer Sciences and Engineering, 2020)
Filtering is an essential part of any signal processing system. This involves estimation of a signal degraded, in most cases, by additive random noise. Several filtering techniques have been proposed where linear processing techniques have been the method of choice for many years because of their simplicity. Most of these techniques, however, assume a Gaussian model for the statistical characteristics of the underlying process and try to optimize the parameters of a system for this model. Nonlinear techniques have recently assumed significance as they are able to suppress noise to preserve important signal elements such as edges and fine details and eliminate degradations occurring during signal formation or transmission through nonlinear channels. A detailed literature survey has been done here to compare these conventional image filters with a iterative approach. This paper includes an analysis about the significance of iteration based approach for image filtering.