摘要
随着红外诱饵技术的不断发展,对传统的小目标识别提出了新的挑战。通过对飞行目标和红外诱饵光谱特征的分析,利用红外多谱段图像对天空背景中具有伴飞诱饵干扰的小目标进行识别。提出了自适应阈值分割和能量相关滤波相结合的方法对图像进行预处理,再利用光谱角算法对疑似小目标进行识别,增加了目标识别的可靠性,降低了算法的复杂度。与传统的单波段目标识别跟踪算法不同,该算法从光谱特征差异性角度对目标进行识别,识别概率高,运算量小,为红外小目标识别提供了新的解决办法。
With the development of the infrared decoy technology,the new challenge is brought for the traditional small-target recognition.In this paper,the spectral characteristics for flying object and infrared decoy were analyzed to identify small targets with infrared decoy interference in the infrared multi-spectral images in sky background.A preprocessing algorithm was proposed,which combined adaptive threshold segmentation with energy correlation filtering.Then,the spectral angle algorithm was used to identify suspected small targets.The reliability of target identification was increased,and the complexity of the algorithm was reduced.Compared with the traditional target identification and tracking algorithm in single band,the proposed algorithm solves the problem from spectral characteristics difference,with higher identification probability and lower computation.This paper provides a new solution in infrared small target identification area.
出处
《红外与激光工程》
EI
CSCD
北大核心
2010年第4期772-776,共5页
Infrared and Laser Engineering
基金
国家自然科学基金资助项目(60877065)
关键词
目标识别
多谱段
自适应阈值分割
能量相关滤波
光谱角
Target identification
Multi-spectral
Adaptive threshold segmentation
Energy correlation filtering
Spectral angle
