An Image Denoising Technique Using NAFSM with Evolutionary Algorithm
Anjali Ojha, Nirupama Tiwari · 2015
In this study, we displayed Satellite Image denoising which is based on noise-adaptive fuzzy switching median filter with Strength Pareto Evolutionary Algorithm (SPEA2). In this algorithm, we worked on three types of noise: Gaussian white noise, Salt and Pepper noise and Poisson noise. There are some picture upgrade calculations to facilitate the impacts of noise over the picture to watch the subtle elements and accumulate noteworthy data. A few calculations acknowledge heaps of parameters from the client to accomplish the best results. In the system for denoising, there is dependably a battle between the noise reduction and the fine safeguarding. We figured the peak signal noise ratio (PSNR), structural similarity matrix (SSIM), execution time and mean square error (MSE) for indicating conserved in our system. We accomplished great results when contrasted with past methodologies. In the past work, they calculated optimization value, however, it gave good PSNR value, but the final noise free image was not good. In our methodology, we work on both gray and color images. In the experimental results, we restored the original image with their quality preservation.