同质性(统计学)
红外线的
计算机科学
分割
度量(数据仓库)
人工智能
模式识别(心理学)
生物系统
光学
物理
数据挖掘
机器学习
生物
作者
Jinyan Nie,Shaocheng Qu,Yantao Wei,Liming Zhang,Lizhen Deng
标识
DOI:10.1016/j.infrared.2018.03.006
摘要
Infrared (IR) small target detection plays an important role in the field of image detection area owing to its intrinsic characteristics. This paper presents a multiscale local homogeneity measure (MLHM) for infrared small target detection, which can enhance the performance of IR small target detection system. Firstly, intra-patch homogeneity of the target itself and the inter-patch heterogeneity between target and the local background regions are integrated to enhance the significant of small target. Secondly, a multiscale measure based on local regions is proposed to obtain the most appropriate response. Finally, an adaptive threshold method is applied to small target segmentation. Experimental results on three different scenarios indicate that the MLHM has good performance under the interference of strong noise.
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