De-noising of images from salt and pepper noise using hybrid filter, fuzzy logic noise detector and genetic optimization algorithm (HFGOA)

The main objective of image de-noising is to remove the noise present in the noisy image. Like that, main objective of proposed methodology is to restore the impulse noised standard test image based on hybrid filter, fuzzy logic system and genetic algorithm. The proposed HFGOA method consists of three steps. In the first step noisy image is de-noised using mean filter and median filter, individually. In the second step the difference vector is calculated using two filters output then it is given as input to fuzzy logic system. Fuzzy rules were generated from the difference vector value using triangular membership function. In the third step using genetic optimization algorithm optimal rule will be selected. Fitness value (PSNR) calculated for each population. The new population was repeatedly created using genetic operator until getting best fitness value. The performance of the proposed method was measured using PSNR value. HFGOA method is tested over standard test image (lena image) for different percentage of salt and pepper noise. The Experimental results of HFGOA method is compared with results of different exiting filters. An experimental result shows the HFGOA method rectifies the drawbacks of exiting filters and increases the visual quality of the image by increasing the PSNR value.