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Denoising Process Based on Arbitrarily Shaped Windows
Huda Al-Ghaib, Reza Adhami
Pages - 304 - 310     |    Revised - 31-10-2015     |    Published - 30-11-2015
Volume - 9   Issue - 6    |    Publication Date - November / December 2015  Table of Contents
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KEYWORDS
Region Merging, Wavelet Transform, Image Denoising, Noise Estimation, Wavelet Shrinkage Process.
ABSTRACT
Many factors, such as moving objects, introduce noise in digital images. The presence of noise affects image quality. The image denoising process works on reconstructing a noiseless image and improving its quality. When an image has an additive white Gaussian noise (AWGN) then denoising becomes a challenging process. In our research, we present an improved algorithm for image denoising in the wavelet domain. Homogenous regions for an input image are estimated using a region merging algorithm. The local variance and wavelet shrinkage algorithm are applied to denoise each image patch. Experimental results based on peak signal to noise ratio (PSNR) measurements showed that our algorithm provided better results compared with a denoising algorithm based on a minimum mean square error (MMSE) estimator.
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Dr. Huda Al-Ghaib
Assistant Professor/Computer Science/Technology and Computing Utah Valley University Orem, 84058, USA - United States of America
Huda.Ghaib@uvu.edu
Professor Reza Adhami
University of Alabama in Huntsville - United States of America