Share Email Print
cover

Proceedings Paper

Bandelet-based image fusion: a comparative study for multi-focus images
Author(s): Michael Giansiracusa; Adam Lutz; Neal Messer; Soundararajan Ezekiel; Erik Blasch; Mark Alford
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

There is a strong initiative to maximize visual information in a single image for viewing by fusing the salient data from multiple images. Many multi-focus imaging systems exist that would be able to provide better image data if these images are fused together. A fused image would allow an analyst to make decisions based on a single image rather than crossreferencing multiple images. The bandelet transform has proven to be an effective multi-resolution transform for both denoising and image fusion through its ability to calculate geometric flow in localized regions and decompose the image based on an orthogonal basis in the direction of the flow. Many studies have been done to develop and validate algorithms for wavelet image fusion but the bandelet has not been well investigated. This study seeks to investigate the use of the bandelet coefficients versus wavelet coefficients in modified versions of image fusion algorithms. There are many different methods for fusing these coefficients together for multi-focus and multi-modal images such as the simple average, absolute min and max, Principal Component Analysis (PCA) and a weighted average. This paper compares the image fusion methods with a variety of no reference image fusion metrics including information theory based, image feature based and structural similarity based assessments.

Paper Details

Date Published: 31 May 2016
PDF: 8 pages
Proc. SPIE 9841, Geospatial Informatics, Fusion, and Motion Video Analytics VI, 98410F (31 May 2016); doi: 10.1117/12.2224329
Show Author Affiliations
Michael Giansiracusa, Indiana Univ. of Pennsylvania (United States)
Adam Lutz, Indiana Univ. of Pennsylvania (United States)
Neal Messer, Indiana Univ. of Pennsylvania (United States)
Soundararajan Ezekiel, Indiana Univ. of Pennsylvania (United States)
Erik Blasch, Air Force Research Lab. (United States)
Mark Alford, Air Force Research Lab. (United States)


Published in SPIE Proceedings Vol. 9841:
Geospatial Informatics, Fusion, and Motion Video Analytics VI
Matthew F. Pellechia; Kannappan Palaniappan; Peter J. Doucette; Shiloh L. Dockstader; Gunasekaran Seetharaman; Paul B. Deignan, Editor(s)

© SPIE. Terms of Use
Back to Top