Adaptive regularized scheme for remote sensing image fusion

作     者：Sizhang TANG Chaomin SHEN Guixu ZHANG 

作者机构：Shanghai Key Laboratory of Multidimensional Information Processing and Department of Computer Science and Technology East China Normal University Shanghai 200241 China Department of Information and Computer Science Shanghai Business School Shanghai 201400 China 

出 版 物：《Frontiers of Earth Science》 (地球科学前沿（英文版）)

年 卷 期：2016年第10卷第2期

页      面：236-244页

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0708[理学-地球物理学] 0802[工学-机械工程] 0835[工学-软件工程] 0704[理学-天文学] 081002[工学-信号与信息处理] 080201[工学-机械制造及其自动化] 

基　　金：This work was supported by the National Basic Research Program of China (No. 2011 CB707104) and the National Natural Science Foundation of China (Grant No. 61273298) 

主　　题：remote sensing image fusion adaptive reg-ulariser variational method steepest descent method 

摘      要：We propose an adaptive regularized algorithm for remote sensing image fusion based on variational methods. In the algorithm, we integrate the inputs using a ＂grey world＂ assumption to achieve visual uniformity. We propose a fusion operator that can automatically select the total variation （TV）-LI term for edges and L2-terms for non-edges. To implement our algorithm, we use the steepest descent method to solve the corresponding Euler-Lagrange equation. Experimental results show that the proposed algorithm achieves remarkable results.