高技术通讯2012，Vol.22Issue(7)：772-777,6.DOI:10.3772/j.issn.1002-0470.2012.07.016
基于级联分类器的红外弱小目标快速检测
Fast detection of small infrared targets based on cascade classification
摘要
Abstract
To solve the problem that small infrared target detection in large images takes much time, a multi-stage algorithm is proposed, which first of all considers local extrema of gray intensity in a whole image as candidate targets, then extracts the features in the neighborhood of the candidates, and finally identifies true targets in the feature space. According to the features of small targets, a feature of gray intensity distribution is presented, with which candidate targets are extracted, and then an algorithm named weighted logistic regression is proposed. Consequently , the detection problem is converted to a binary classification problem in the feature space. The experimental results show that the proposed algorithm has the good performance for real-time target detection with low SNR images.关键词
红外小目标/检测/灰度分布特征/加权逻辑斯蒂回归Key words
small infrared target/detection/feature of gray intensity distribution/weighted logistic regression引用本文复制引用
许庆晗,金立左,费树岷..基于级联分类器的红外弱小目标快速检测[J].高技术通讯,2012,22(7):772-777,6.基金项目
航空科学基金(20080169003,20115169016)资助项目. （20080169003,20115169016）
