基于假设检验的红外弱小目标感兴趣区域提取算法  

ROI Detection Algorithm for Small Infrared Target in Infrared Image Based on Hypothesis Testing

作　　者：产启文[1] 

机构地区：[1]上海海事大学,上海200135

出　　处：《红外》2011年第8期29-34,共6页Infrared

摘　　要：根据假设检验的基本原理,提出了一种红外弱小目标感兴趣区域检测算法。该方法首先按照最小错误概率准则抽取图像中目标的感兴趣区域,然后在这些区域里进行目标提取和分析。实验结果表明,该方法很好地克服了一些传统方法中冗余计算多和分析难度高等缺点,非常适合于红外弱小目标的高性能检测。According to the basic principle of hypothesis testing,an algorithm for detecting the region of interest（ROI） of a small infrared target in an image is proposed.In the method,the ROI of a small infrared target in an image is firstly extracted by using the minimum error probability criterion and then target extraction and analysis are carried out in those regions of interest.The experimental result shows that this method overcomes the disadvantages such as large computation and difficult analysis in traditional methods and is very suitable for the high performance detection of small infrared targets in infrared images.

关 键 词：感兴趣区域 最小错误概率准则 假设检验 红外序列 小目标检测 

分 类 号：TP274.52[自动化与计算机技术—检测技术与自动化装置]