By Topic

A spatial feature enhanced MMI algorithm for multi-modal wild-fire 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

2 Author(s)
Xiaofeng Fan ; Chester F. Carlson Center for Imaging Sci., Rochester Inst. of Technol., Rochester, NY ; Rhody, H.E.

The integration of multi-spectral airborne imagery and geographic data for wildfire and emergency response requires 3D multiple view registration. Registration of maps, visible imagery and IR imagery, especially LWIR, is challenging because of the difference in brightness, color and features that are available in the different modalities. We have developed a semi-automated workflow for the registration and exploitation of this imagery and data that can produce quick-turnaround products for research and wildfire management. The technique is based upon an enhancement of the conventional maximization of mutual information. This technique largely overcomes the problems that arise from uncorrelated variations in pixel intensity between visible sensors, LWIR sensors that respond to temperature variations, and artificial colorations present in maps. A measure of registration confidence based upon the kurtosis of search space has been developed to enable operators to be cued to examine suspicious result produced by the semi-automated workflow algorithms. Experiments on real wild-fire imagery demonstrate the performance of the technique.

Published in:

Applied Imagery Pattern Recognition Workshop, 2008. AIPR '08. 37th IEEE

Date of Conference:

15-17 Oct. 2008