SPECKLE NOISE REDUCTION BY USING WAVELETS
Amandeep Kaur, Karamjeet Singh · 2010
Abstract: In image processing, image is corrupted by different type of noises. But generally medical image is corrupted by speckle noise. So image de-noising has become a very essential exercise all through the diagnose. Noises are of two type additive and multiplicative noise. Speckle noise is multiplicative noise, so it’s difficult to remove the multiplicative noise as compared to additive noise. The traditional techniques are not very good for especially speckle noise reduction. So we have focused on speckle noise reduction using wavelets. In this paper, we present image de-noising procedure by using wavelet based techniques. Wavelet based techniques has been explored and used for speckle noise reduction. The results obtained by the wavelets based techniques are compared with other speckle noise reduction techniques to demonstrate its higher performance for speckle noise reduction. Keywords: speckle noise, lee, frost, kaun, SRAD, wavelets. 1. INTRODUCTION An image is often corrupted by noise since its acquisition or transmission. The goal of de-noising is to remove the noise while retaining as much as possible the important signal features of an image. Traditionally, this is achieved by linear processing such as Wiener filtering [1]-[3]. A vast literature has emerged recently on signal de-noising using nonlinear techniques, in the setting of additive white Gaussian noise. The image analysis process can be broken into three primary stages which are pre-processing, data reduction, and features analysis. Removal of noise from an image is the one of the important tasks in image processing. Depending on nature of the noise, such as additive or multiplicative noise, there are several approaches for removal of noise from an image [1] -[2]. lines in the image. Weiner filter was adopted for