Infrared small target detection based on density peaks searching and weighted multi-feature local difference  

作　　者：JI Bin FAN Pengxiang WANG Mengli LIU Yang XU Jiafeng 

机构地区：[1]School of Computer Science and Technology,Anhui University of Technology,Maanshan 243032,China

出　　处：《Optoelectronics Letters》2025年第4期218-225,共8页光电子快报(英文版)

基　　金：supported by the National Natural Science Foundation of China (No.52205548)。

摘　　要：To address the issues of unknown target size,blurred edges,background interference and low contrast in infrared small target detection,this paper proposes a method based on density peaks searching and weighted multi-feature local difference.Firstly,an improved high-boost filter is used for preprocessing to eliminate background clutter and high-brightness interference,thereby increasing the probability of capturing real targets in the density peak search.Secondly,a triple-layer window is used to extract features from the area surrounding candidate targets,addressing the uncertainty of small target sizes.By calculating multi-feature local differences between the triple-layer windows,the problems of blurred target edges and low contrast are resolved.To balance the contribution of different features,intra-class distance is used to calculate weights,achieving weighted fusion of multi-feature local differences to obtain the weighted multi-feature local differences of candidate targets.The real targets are then extracted using the interquartile range.Experiments on datasets such as SIRST and IRSTD-IK show that the proposed method is suitable for various complex types and demonstrates good robustness and detection performance.

关 键 词：extract featur background clutter density peaks searching infrared small target detection weighted multi feature local difference capturing real targets density peak infrared small target detectionthis 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]