By Topic

Fusion of infrared and visible images using empirical mode decomposition and spatial opponent processing

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)
Paterne Sissinto ; Department of Electrical and Computer Engineering, Morgan State University, 1700 E. Cold Spring Lane, Baltimore MD 21239, USA ; Jumoke Ladeji-Osias

Infrared (IR) cameras capture thermal radiations emitted by objects in a scene while Electro-Optical (EO) cameras picture reflected colors from a scene. These sources of different modalities produce complementary data of the same panorama. In aeronautics, medical imaging and rescue operations, these sensors are often utilized simultaneously. The objective of this work is to integrate the content of both streams in order to deliver a unique image presenting more visual cues than any of the originals taken separately. To reach that goal, the synthesis of a robust algorithm is required. The Empirical Mode Decomposition (EMD) decomposes image signals into Intrinsic Mode Functions (IMFs). In this paper, we proposed a novel approach that integrates the IR and EO IMFs using principles of neural science for multi-spectral fusion. We show how to integrate IR and EO information utilizing spatial opponent processing. We report the performance on images from Octec ltd and compare our result to their Wavelet-based fusion output. Mutual Information is the metric employed for fusion quality assessment in this work. Positive results have been obtained for tests conducted on IR and EO images containing complementary information.

Published in:

2011 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)

Date of Conference:

11-13 Oct. 2011