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

New Method of Probability Density Estimation with Application to Mutual Information Based Image Registration

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)
Rajwade, A. ; University of Florida, USA ; Banerjee, A. ; Rangarajan, A.

We present a new, robust and computationally efficient method for estimating the probability density of the intensity values in an image. Our approach makes use of a continuous representation of the image and develops a relation between probability density at a particular intensity value and image gradients along the level sets at that value. Unlike traditional sample-based methods such as histograms, minimum spanning trees (MSTs), Parzen windows or mixture models, our technique expressly accounts for the relative ordering of the intensity values at different image locations and exploits the geometry of the image surface. Moreover, our method avoids the histogram binning problem and requires no critical parameter tuning. We extend the method to compute the joint density between two or more images. We apply our density estimation technique to the task of affine registration of 2D images using mutual information and show good results under high noise.

Published in:

Computer Vision and Pattern Recognition, 2006 IEEE Computer Society Conference on  (Volume:2 )

Date of Conference:

2006

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.