基于多滤波算法融合的红外小目标检测  

Detection of infrared small target based on fusion of multi-filters

作　　者：王东[1] 王敏[1] 

机构地区：[1]华中科技大学自动化学院,湖北武汉430074

出　　处：《应用光学》2017年第1期106-113,共8页Journal of Applied Optics

基　　金：国家自然科学基金(61370180)

摘　　要：针对海天背景下红外视频图像序列中小目标检测的精度问题,提出一种基于多滤波融合的算法。通过分析红外小目标及背景噪声的成像特征与时空特性,将Tophat算法与改进的Robinson guard滤波器相结合,有效抑制背景、突显目标;采用自适应阈值分割提取候选目标,并使用Unger平滑滤波以及多目标关联滤波剔除噪声和伪目标。多组红外小目标图像序列的检测实验结果表明,提出的算法平均检测率高达99%,在不同场景下均有较高的检测精度。Aiming at solving accuracy problem of infrared small target detection in sky and ocean background scenarios of infrared image sequences, a novel infrared small target detection based on multi-filters algorithm fusion method is presented in this paper. Firstly infrared small target and imaging, time and space characteristics of the corresponding background noise are analyzed. Tophat algorithm with improved Robinson guard filter are then integrated to highlight target and suppress clutter background by using infrared small target imaging features. Adap- tive threshold segmentation is used to extract candidate targets, while Unger smoothing filter and multi-objects association filter are used to eliminate random noise and false targets in the candidate targets. Multiple experiments of infrared small target image sequences are implemented, and experimental results show that proposed method can detect infrared small targets at 99 % detection rate with high reliability and good real-time performance.

关 键 词：多滤波融合 红外小目标检测 Tophat算法 ROBINSON guard滤波器算法 自适应阈值分割 Unger平滑滤波 多目标关联滤波 

分 类 号：TN215[电子电信—物理电子学] TP391[自动化与计算机技术—计算机应用技术]