Abstract
Objectives: This paper is providing a comparative performance analysis of wavelet denoising with Gaussian filter applied on images contaminated with various noises. Gaussian filter is a basic filter used in image processing. Its response is varying with its kernel sizes that have also been shown in analysis. Wavelet based de-noising is also one of the way of removing various noises usually present in images. Wavelet transform is used to convert the images to wavelet domain. Based on thresholding operations in wavelet domain noise could be removed from images. Methods/Analysis: In this paper, image quality matrices like PSNR and MSE have been compared for the various types of noises in images for different denoising methods. Moreover, the behavior of different methods for image denoising have been graphically shown in paper with MATLAB based simulations. Findings: In the end wavelet based de-noising methods has been compared with Gaussian based filter. The paper provides a review of filters and their denoising analysis under different noise conditions.
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