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

Multifocus image fusion algorithm using iterative segmentation based on edge information and adaptive threshold

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

4 Author(s)
Shah, P. ; Dept. of Electr. Eng., IIT Bombay, Mumbai, India ; Kumar, A. ; Merchant, S.N. ; Desai, U.B.

This paper presents algorithm for multifocus image fusion in spatial domain based on iterative segmentation and edge information of the source images. The basic idea is to divide the images into smaller blocks, gather edge information for each block and then select the region with greater edge information to construct the resultant `all-in-focus' fused image. To improve the fusion quality further, an iterative approach is proposed. Each iteration selects the regions in focus with the help of an adaptive threshold while leaving the remaining regions for analysis in the next iteration. A further enhancement in the technique is achieved by making the number of blocks and size of blocks adaptive in each iteration. The pixels which remain unselected till the last iteration are then selected from the source images by comparison of the edge activities in the corresponding segments of the source images. The performance of the method have been extensively tested on several pairs of multifocus images and compared quantitatively with existing methods. Experimental results show that the proposed method improves fusion quality by reducing loss of information by almost 50% and noise by more than 99%.

Published in:

Information Fusion (FUSION), 2012 15th International Conference on

Date of Conference:

9-12 July 2012

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.