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Entropy 2014, 16(11), 6099-6115; doi:10.3390/e16116099

Image Fusion Based on the \({\Delta ^{ - 1}} - T{V_0}\) Energy Function

1
Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China
2
Research Center for Smart Vehicles, Toyota Technological Institute, Nagoya, Aichi 468-8511, Japan
3
Department of General Education, Macau University of Science and Technology, Macau, China
4
Toyota Central R&D Labs, Yokomichi, Aichi 480-1192, Japan
*
Author to whom correspondence should be addressed.
Received: 9 October 2014 / Revised: 11 November 2014 / Accepted: 12 November 2014 / Published: 18 November 2014
(This article belongs to the Section Information Theory)
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Abstract

This article proposes a \({\Delta^{-1}}-T{V_0}\) energy function to fuse a multi-spectral image with a panchromatic image. The proposed energy function consists of two components, a \(TV_0\) component and a \(\Delta^{-1}\) component. The \(TV_0\) term uses the sparse priority to increase the detailed spatial information; while the \({\Delta ^{ - 1}}\) term removes the block effect of the multi-spectral image. Furthermore, as the proposed energy function is non-convex, we also adopt an alternative minimization algorithm and the \(L_0\) gradient minimization to solve it. Experimental results demonstrate the improved performance of the proposed method over existing methods. View Full-Text
Keywords: image fusion; inverse transform of the Laplace operator (\(\Delta^{-1}\) ); sparse norm; total variation image fusion; inverse transform of the Laplace operator (\(\Delta^{-1}\) ); sparse norm; total variation
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Xie, Q.; Ma, C.; Guo, C.; John, V.; Mita, S.; Long, Q. Image Fusion Based on the \({\Delta ^{ - 1}} - T{V_0}\) Energy Function. Entropy 2014, 16, 6099-6115.

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