Soft Computing Techniques for Noise Filtration in the Image Recognition Processes

In this paper, methods for noise filtration in the image recognition processes are considered. The following noise filtration methods were analyzed: arithmetic averaging filter, geometric averaging filter, median filtering, adaptive median filtration, Gaussian filtration and filtration using soft computing techniques, in particular the fuzzy color preserving Gaussian noise reduction method (FCG filter). Besides, the different types of noise that may occur on a digital image are discussed. All methods were evaluated using metrics like mean squared error (MSE), peak signal-to-noise ratio (PSNR) and structure similarity of images (SSIM). It has been found that all of the above methods can well filter out only a certain type of noise. In this paper, a combination of adaptive median filtering and FGG filter is proposed for removal of combined pulse and Gaussian noises.