Performance Comparison of Infrared and Visible Image Fusion Approaches

被引：0

作者：

Lee, Myung-Won ^{[1
]}

Kwak, Keun-Chang ^{[1
]}

机构：

[1] Chosun Univ, Dept Control & Instrumentat Engn, Gwangju, South Korea

来源：

2017 INTERNATIONAL CONFERENCE ON CONTROL, ARTIFICIAL INTELLIGENCE, ROBOTICS & OPTIMIZATION (ICCAIRO) | 2017年

关键词：

infrared image; visible image; image registration; image fusion; sparse representation; TRANSFORM; DECOMPOSITION;

D O I：

10.1109/ICCAIRO.2017.58

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we perform the performance comparison of image fusion methods from infrared and visible images. Here, we first use intensity-based registration method that image is aligned based on the relative intensity patterns for image registration. We also compare the performances of Sparse Representation (SR)-based and Multiscale Transform (MST)-based image fusion algorithms from OSU color-thermal database. Finally, we evaluate performance index by mutual information and entropy from final fusion images. It was found from the results that the presented image registration and fusion methods showed good performances.

引用

页码：274 / 277

页数：4

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