By Topic

A New Automated Quality Assessment Algorithm for Night Vision Image Fusion

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)
Yin Chen ; ECE Department, Lehigh University, Bethlehem, PA 18015, Email: ; Rick S. Blum

In this paper we propose a perceptual quality evaluation method for image fusion which is based on human visual system (HVS) models. Our method assesses the image quality of a fused image using the following steps. First the source and fused images are filtered by a contrast sensitivity function (CSF) after which a local contrast map is computed for each image. Second, a contrast preservation map is generated to describe the relationship between the fused image and each source image. Finally, the preservation maps are weighted by a saliency map to obtain an overall quality map. The mean of the quality map indicates the quality for the fused image. Experimental results compare the predictions made by our algorithm with human perceptual evaluations for several different parameter settings in our algorithm. For some specific parameter settings, we find our algorithm provides better predictions, which are more closely matched to human perceptual evaluations, than the existing algorithms.

Published in:

2007 41st Annual Conference on Information Sciences and Systems

Date of Conference:

14-16 March 2007