Cart (Loading....) | Create Account
Close category search window
 

Spatially adaptive denoising algorithm for a single image corrupted by gaussian noise

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Tuan-Anh Nguyen ; Soongsil Univ., Seoul, South Korea ; Won-Seon Song ; Min-Cheol Hong

In this paper, we propose a spatially adaptive denoising algorithm using local statistics for a single image corrupted by Gaussian noise. The proposed algorithm consists of two stages: noise detection and noise removal filtering. To corporate desirable properties into denoising process, local weighted mean, local weighted activity, and local maximum are defined. Using the local statistics, constraint for noise detection is defined. In addition, a modified Gaussian noise removal filter based on the local statistics is used to control the degree of noise suppression. The experimental results demonstrate the capability of the proposed algorithm.

Published in:

Consumer Electronics, IEEE Transactions on  (Volume:56 ,  Issue: 3 )

Date of Publication:

Aug. 2010

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.