基于局部对比度背景估计的红外小目标检测方法  

Infrared small-target detection utilizing background estimation combined with local contrast

作　　者：赵骞 韩金辉 徐茂 陈园园 ZHAO Qian;HAN Jinhui;XU Mao;CHEN Yuanyuan(College of Physics and Telecommunication,Zhoukou Normal University,Zhoukou 466001,China)

机构地区：[1]周口师范学院物理与电信工程学院,河南周口466001

出　　处：《智能系统学报》2022年第2期314-324,共11页CAAI Transactions on Intelligent Systems

基　　金：国家自然科学基金项目(61802455,62003381);河南省重点研发与推广专项(科技攻关)项目(192102210089,212102210525).

摘　　要：为缓解复杂背景对红外小目标检测任务的干扰,提出一种新的红外小目标检测方法。该方法将背景估计与局部对比度相结合,以提高算法的检测性能。提出了一种更适合于小目标检测的双层均值最大化背景估计算法,以获得更准确的基准背景值。在原始图像和估计背景之间提出了比差联合局部对比度度量方法,可以在增强目标的同时抑制各种类型的复杂背景。通过实验对比分析,验证该方法的有效性和鲁棒性。In order to alleviate the interference of complex backgrounds in infrared small target detection,a new in-frared small target detection method is proposed.The new method combines background estimation with local contrast to improve the detection performance of the algorithm.The main work includes the following aspects:First,a double-layer max-mean background estimation algorithm that is more suitable for small target detection is proposed to get a more accurate background benchmark.Then,a ratio-difference joint local contrast measure is proposed between the raw image and the estimated background to enhance the different sizes of true targets while simultaneously suppressing vari-ous types of complex backgrounds.The analysis and comparison in the experiment show its effectiveness and robustness.

关 键 词：红外小目标 最大均值 背景估计 比差联合方法 局部对比度 目标检测 单帧检测 抗噪声能力 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]