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Reseach Article

Image Denoising using Curvelet: an Approach based on Average Fusion

Published on July 2012 by S. Sukumaran, M. Shanmugasundaram
Advanced Computing and Communication Technologies for HPC Applications
Foundation of Computer Science USA
ACCTHPCA - Number 5
July 2012
Authors: S. Sukumaran, M. Shanmugasundaram
d089fc90-84d3-4226-b7f9-af4a4e75bb1a

S. Sukumaran, M. Shanmugasundaram . Image Denoising using Curvelet: an Approach based on Average Fusion. Advanced Computing and Communication Technologies for HPC Applications. ACCTHPCA, 5 (July 2012), 38-42.

@article{
author = { S. Sukumaran, M. Shanmugasundaram },
title = { Image Denoising using Curvelet: an Approach based on Average Fusion },
journal = { Advanced Computing and Communication Technologies for HPC Applications },
issue_date = { July 2012 },
volume = { ACCTHPCA },
number = { 5 },
month = { July },
year = { 2012 },
issn = 0975-8887,
pages = { 38-42 },
numpages = 5,
url = { /specialissues/accthpca/number5/7585-1039/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Advanced Computing and Communication Technologies for HPC Applications
%A S. Sukumaran
%A M. Shanmugasundaram
%T Image Denoising using Curvelet: an Approach based on Average Fusion
%J Advanced Computing and Communication Technologies for HPC Applications
%@ 0975-8887
%V ACCTHPCA
%N 5
%P 38-42
%D 2012
%I International Journal of Computer Applications
Abstract

The most significant task of image processing is to reduce noise which is commonly found in images. In recent years, technology is being improved to analyze the images to get better quality. Since the image gets loss of edge feature and detail information during the process of de-noise, this paper attempts to present and compare a new method based on curvelet transform using image fusion. Results show that this approach has a broad future for removing noise as well as preserving edges of image.

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Index Terms

Computer Science
Information Sciences

Keywords

Curvelet Image Fusion Denoise Multiresolution Ridgelet Gaussian Filter.