Object-based multispectral image fusion method using deep learning

被引：2

作者：

Jang, Hyunsung ^{[1
,2
]}

Ha, Namkoo ^{[1
]}

Yeon, Yoonmo ^{[1
]}

Kwon, Kuyong ^{[1
]}

Gil, Sungho ^{[1
]}

Lee, Seungha ^{[1
]}

Park, Sungsoon ^{[1
]}

Jung, Hyungjoo ^{[2
]}

Sohn, Kwanghoon ^{[2
]}

机构：

[1] LIG Nex1 Co Ltd, Yongin 16911, South Korea

[2] Yonsei Univ, Sch Elect & Elect Engn, Seoul 03722, South Korea

来源：

ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING IN DEFENSE APPLICATIONS | 2019年 / 11169卷

关键词：

Multispectral; Image fusion; Deep learning; Unsupervised learning; Computer vision;

D O I：

10.1117/12.2532718

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The goal of multispectral image fusion is to integrate complementary information from multispectral sensors to enhance human visual perception and object detection. Additionally, there are also cases when only the object needs to be emphasized with minimal background interference. This paper presents an object-based fusion method using deep learning to accomplish this objective. The proposed method uses information regarding the region of an object to perform fusion on the object. As we cannot provide labels for fusion results at the learning stage, we propose an unsupervised learning method. The proposed method simultaneously provides appropriate image information from the background and target for surveillance and reconnaissance.

引用

页数：6

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