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

Robust Impulse Noise Variance Estimation Based on Image Histogram

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)
Yi Wan ; Inst. for Signals & Inf. Process., Lanzhou Univ., Lanzhou, China ; Qiqiang Chen ; Yan Yang

The state of the art impulse noise removal methods make use of the noise variance, or equivalently the noise mixing probability p, and are iterative procedures (e.g., , ). However, so far there has been a lack of effective estimator for p. As a result, true values of p are often used during simulation, which may not be practical. Furthermore, the optimal stopping criteria for the iterative algorithms have been elusive until recently. In a computationally heavy method is proposed for determining the optimal number of iterations. In this letter we make two contributions. We first develop a robust estimator for p by using the empirical observation that a natural image usually doesn't cover all pixel value range, then we design an efficient linear transformation to replace complicated computation of order statistics. Based on this estimated p value, we further derive the formula for estimating the true image histogram, and use it to formulate a new efficient optimal stopping criterion during the iterative denoising process. This formulation has a simple interpretation of its optimality and yields improved denoising performance.

Published in:

Signal Processing Letters, IEEE  (Volume:17 ,  Issue: 5 )

Date of Publication:

May 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.