Conference Proceedings

Abstract

Image denoising algorithms may be the oldest in image processing. A first pre-processing step in analyzing such datasets is denoising, that is, estimating the unknown signal of interest from the available noisy data. There are several different approaches to denoise images. To remove noise several techniques and image denoising filters are used. This paper shows a comparative study and analysis of image denoising techniques relying on fuzzy filters. First is the fuzzy impulse noise detection and reduction method (FIDRM) and second is noise adaptive fuzzy switching median filter for salt and pepper noise reduction (NAFSM). The comparative analysis shows that the NAFSM filter is better then the FIDRM filter in terms of execution time, peak signal to noise ratio (PSNR) and mean square error (MSE).