Image Fusion Based on the Δ−1 –TV0 Energy Function

Entropy

Qiwei Xie¹  Chao Ma²  Chunzhao Guo⁴  Vijay John³  Seiichi Mita³ 

[1] Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; E-Mail:;Department of General Education, Macau University of Science and Technology, Macau, China;Research Center for Smart Vehicles, Toyota Technological Institute, Nagoya, Aichi 468-8511, Japan; E-Mails:;Toyota Central R&D Labs, Yokomichi, Aichi 480-1192, Japan; E-Mail:

关键词: image fusion;    inverse transform of the Laplace operator (Δ⁻¹);    sparse norm;    total variation;   

DOI  :  10.3390/e16116099

来源: mdpi

【 摘 要 】

This article proposes a Δ⁻¹ – TV₀ energy function to fuse a multi-spectral image with a panchromatic image. The proposed energy function consists of two components, a TV₀ component and a Δ⁻¹ component. The TV₀ term uses the sparse priority to increase the detailed spatial information; while the Δ⁻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 L₀ gradient minimization to solve it. Experimental results demonstrate the improved performance of the proposed method over existing methods.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland