加权
对比度(视觉)
度量(数据仓库)
人工智能
计算机科学
a计权
功能(生物学)
滤波器(信号处理)
模式识别(心理学)
对比度
匹配滤波器
算法
计算机视觉
数学
数据挖掘
进化生物学
生物
操作系统
医学
放射科
作者
Jinhui Han,Saed Moradi,Iman Faramarzi,Honghui Zhang,Qian Zhao,Xiaojian Zhang,Nan Li
标识
DOI:10.1109/lgrs.2020.3004978
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.
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