By Topic

Advanced Image Processing Techniques for Maximum Information Recovery

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
$33 $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

2 Author(s)
Jiecai Luo ; Member, IEEE, Department of Electrical Engineering, College of Engineering, Southern University, Baton Rouge, LA 70813 ; James Cross

Some radio frequency and optical sensors collect large-scale sets of spatial imagery data whose content is often obscured by fog, clouds, foliage and other intervening structures. Often, the obstruction is such as to render unreliable the definition of underling images. There are several typical mathematical methods used in image processing to remove interferences from images to include spectral methods, wave front or shock methods, and the use of non-abelian group operations. In this paper, a new advanced image processing technique based on image segmentations has been developed and tested for the removal of fog, clouds, foliage and other interfering structures. The developed method has been applied to certain images to demonstrate its effectiveness in removing unwanted sub-images.

Published in:

2007 Thirty-Ninth Southeastern Symposium on System Theory

Date of Conference:

4-6 March 2007