Adaptive top-hat filter based on quantum genetic algorithm for infrared small target detection

被引：86

作者：

Deng, Lizhen ^{[1
]}

Zhu, Hu ^{[1
]}

Zhou, Quan ^{[1
]}

Li, Yansheng ^{[2
]}

机构：

[1] Nanjing Univ Posts & Telecommun, Coll Telecommun & Informat Engn, Nanjing 210003, Jiangsu, Peoples R China

[2] Wuhan Univ, Sch Remote Sensing & Informat Engn, Wuhan 430079, Hubei, Peoples R China

来源：

MULTIMEDIA TOOLS AND APPLICATIONS | 2018年 / 77卷 / 09期

基金：

中国博士后科学基金;

关键词：

Infrared small target detection; Top-hat filter; Quantum genetic algorithm; Convergence analysis; DESIGN;

D O I：

10.1007/s11042-017-4592-2

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

With the development of infrared technology, infrared small targets detection has attracted great interest of researchers. Top-hat filter is one of widely used methods for detecting infrared small target, and the structure elements have great influence on the performance of detection. The structure elements are desired to be adjusted adaptively. To this end, an adaptive structure elements optimization method based on quantum genetic algorithm (QGA) is introduced, and the convergence of QGA reveals the effectiveness of QGA. Experimental results show that the proposed adaptive top-hat filter based on QGA can achieve more stable infrared small target detection performance compared with the traditional top-hat filter.

引用

页码：10539 / 10551

页数：13

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