Comparative Study on Fuzzy Logic Based Mixed Noise Filter for Colour Images
M. Syed Mohamed Ibrahim, S. Abdul Saleem · 2014
The objective of this project is to denoise the color images. This project denoises the images which are only affected by the Gaussian, Impulse and mixed Gaussian-impulse noise. In this project a new filter is used to remove the noise. This filter uses the fuzzy peer group concept to remove the noise. The fuzzy peer group extends the peer group concept in the fuzzy setting. A fuzzy peer group will be defined as a fuzzy set that takes a peer group as support set. The fuzzy peer group of each image pixel will be determined by means of a novel fuzzy logic-based procedure. The fuzzy peer group concept is used to design a twostep color image filter. Cascading a fuzzy rule-based filter which is designed to remove the impulsive noise. Fuzzy average filtering is designed to remove the Gaussian noise. The performance of this filter is compared to the fuzzy logic based adaptive filter noise filter. Peak-Signalto-Noise-Ratio, Mean Square Error and Root Mean Square Error metric are used to measure the performance of the denoising filter