基于小波包变换的红外弱小目标检测  

Infrared Dim Small Target Detection Based on Wavelet Packet Transform

作　　者：冯洋[1] FENG Yang(School of Physics and Electrical Engineering,Weinan Normal University,Weinan 714000,China)

机构地区：[1]渭南师范学院物理与电气工程学院,陕西渭南714000

出　　处：《计算机与现代化》2020年第12期112-115,122,共5页Computer and Modernization

基　　金：陕西省教育厅专项科学研究项目(17JK0271)。

摘　　要：针对复杂背景下红外弱小目标的检测问题,提出一种基于小波包变换的红外弱小目标检测算法。该算法首先采用小波包变换对含有弱小目标的红外图像进行多尺度分解,得到不同尺度下的高低频节点系数;其次根据不同节点系数重构时对目标能量贡献的不同,选取高频频带中能量分布居中的频带节点系数对图像进行重构完成背景抑制;最后对重构后的目标图像采用自适应阈值分割方法进行目标分割,得到目标检测结果。实验采用多组红外序列图像进行验证,仿真结果表明:该算法可以很好地抑制背景和云层边缘,精确地检测出目标信号,同时提高了目标的信杂比和对比度等参数。For the detection of infrared dim small targets under complex background,an infrared dim small targets detection algorithm based on wavelet packet transform is proposed.Firstly,the wavelet packet transform is used to decompose the infrared image with small and weak targets to obtain the high and low frequency node coefficients at different scales.Secondly,according to the different contributions to the target energy during the reconstruction of different node coefficients,the frequency band node coefficients in the middle of the energy distribution in the high frequency band are selected to reconstruct the image to complete the background suppression.Finally,the target image after reconstruction is segmented by adaptive threshold segmentation method,and the result of target detection is obtained.In the experiment,multiple infrared sequence images were used to verify the results.The simulation results show that the algorithm can suppress the background and cloud edge well,detect the target signal accurately,and improve the target’s signal-to-clutter ratio and contrast.

关 键 词：图像处理 红外图像 目标检测 背景抑制 小波包变换 

分 类 号：TN911.73[电子电信—通信与信息系统]