Image Denoising by Wavelet Transform for Mixed Noise.

Abstract

Image denoising is a very familiar technique which is used to remove the all unwanted noises from the original image. There are various methods to remove noise from digital images. In this paper we use Discrete Wavelet Transform for this purpose. In wavelet transform, there are two types of thresholding-Hard thresholding and Soft thresholding. We take a building image to describe the denoising process. First we add different types of noises in our image and then we apply the different thresholdings of DWT. We also use combination of both thresholdings in this paper to denoise the noisy image. To compare the denoised images with the noisy image, we take some performance parameters which are as follows; Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Structural Similarity Index (SSIM). We use MATLAB for simulation purpose.