Infrared Small Target Detection Based on the Weighted Strengthened Local Contrast Measure

被引:162
|
作者
Han, Jinhui [1 ]
Moradi, Saed [2 ]
Faramarzi, Iman [3 ]
Zhang, Honghui [1 ]
Zhao, Qian [1 ]
Zhang, Xiaojian [1 ]
Li, Nan [1 ]
机构
[1] Zhoukou Normal Univ, Coll Phys & Telecommun Engn, Zhoukou 466001, Peoples R China
[2] Univ Isfahan, Dept Elect Engn, Esfahan 81774673441, Iran
[3] Malek E Ashtar Univ Technol, Fac Elect & Comp Engn, Tehran 158751744, Iran
基金
中国国家自然科学基金;
关键词
Estimation; Object detection; Weight measurement; Complexity theory; Kernel; Shape; Dogs; Improved regional intensity level (IRIL); infrared (IR) small target; strengthened local contrast measure (SLCM); weighting function; DIM; FRAMEWORK;
D O I
10.1109/LGRS.2020.3004978
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
In this letter, a weighted strengthened local contrast measure (WSLCM) algorithm for infrared (IR) small target detection is proposed, it consists of two modules, the strengthened local contrast measure (SLCM), and the weighting function. In the SLCM calculation, the ideas of matched filter and background estimation are adopted to enhance true target and suppress complex background, then both ratio and difference operations are used to calculate the SLCM. In the weighting function definition, three components are considered: the characteristics of the target, the characteristics of the background, and the difference between them. Especially, an improved regional intensity level (IRIL) algorithm is proposed to evaluate the complexity of a cell, thus it can suppress random noises better. Experiments on some real IR images show that the proposed WSLCM can achieve a better detection performance under complex background.
引用
收藏
页码:1670 / 1674
页数:5
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