Image fusion based on TV -L1-convex constrained algorithm

Qiwei Xie, Qian Long, S. Mita, X. Chen, A. Jiang
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引用次数: 1

Abstract

This paper solves the fusion problem by TV - L1-convex constrained algorithm. The energy function mainly consists of three components. One part ensures injection of more correlated detailed spatial information using total variation method. Another part preserves the spectral information through L1 norm based on data fitting term. The third part is consisted of three convex constrained conditions, which ensure that the result is proper. Because the energy function is non-smooth, we use the split Bregman algorithm to solve it. Experimental result demonstrates the superiority of the proposed method over some classical methods.
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基于TV - l1 -凸约束算法的图像融合
本文采用TV - l1 -凸约束算法解决了融合问题。能量函数主要由三部分组成。一部分是利用全变分法确保注入更多相关的详细空间信息。另一部分通过基于数据拟合项的L1范数保留谱信息。第三部分由三个凸约束条件组成,保证了结果的正确性。由于能量函数是非光滑的,我们采用了分裂Bregman算法来求解。实验结果表明,该方法优于一些经典方法。
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