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Proceedings Paper

Optimal multi-focus contourlet-based image fusion algorithm selection
Author(s): Adam Lutz; Michael Giansiracusa; Neal Messer; Soundararajan Ezekiel; Erik Blasch; Mark Alford
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Paper Abstract

Multi-focus image fusion is becoming increasingly prevalent, as there is a strong initiative to maximize visual information in a single image by fusing the salient data from multiple images for visualization. This allows an analyst to make decisions based on a larger amount of information in a more efficient manner because multiple images need not be cross-referenced. The contourlet transform has proven to be an effective multi-resolution transform for both denoising and image fusion through its ability to pick up the directional and anisotropic properties while being designed to decompose the discrete two-dimensional domain. Many studies have been done to develop and validate algorithms for wavelet image fusion, but the contourlet has not been as thoroughly studied. When the contourlet coefficients for the wavelet coefficients are substituted in image fusion algorithms, it is contourlet image fusion. There are a multitude of methods for fusing these coefficients together and the results demonstrate that there is an opportunity for fusing coefficients together in the contourlet domain for multi-focus images. This paper compared the algorithms with a variety of no reference image fusion metrics including information theory based, image feature based and structural similarity based assessments to select the image fusion method.

Paper Details

Date Published: 31 May 2016
PDF: 8 pages
Proc. SPIE 9841, Geospatial Informatics, Fusion, and Motion Video Analytics VI, 98410E (31 May 2016); doi: 10.1117/12.2224325
Show Author Affiliations
Adam Lutz, Indiana Univ. of Pennsylvania (United States)
Michael Giansiracusa, 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)

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