一种新的红外复杂背景自适应抑制算法  

New adaptive infrared strong cluttered background suppression algorithm

作　　者：汪大宝[1] 刘上乾[1] 张峰[1] 

机构地区：[1]西安电子科技大学技术物理学院,陕西西安710071

出　　处：《西安电子科技大学学报》2010年第5期927-933,共7页Journal of Xidian University

基　　金：国家自然科学基金资助项目(60377034)

摘　　要：为了解决低信噪比非平稳复杂云层背景下红外弱小目标检测问题,提出了一种新的基于Facet模型的正则化双向扩散滤波算法.该算法采用Facet模型拟合图像曲面,并设计了平均方向导数梯度算子描述拟合图像曲面的多向梯度特征,以准确识别目标和背景的特征差别.结合平均方向导数梯度算子,设计了一种新的正则化双向扩散背景抑制技术.与传统算法相比,这种算法能够依据目标和背景的特征差别自适应地在前向扩散(目标增强)和后向扩散(背景抑制)之间切换,以实现在抑制背景杂波的同时增强目标.理论分析和实验结果表明,这种算法对包含强纹理结构的非平稳复杂云层背景杂波具有良好的抑制作用,并且算法结构简单,运算量小,易于硬件实时实现.Aiming at the difficulty of detecting infrared week-dim targets against the nonstationary strong cluttered background in an infrared image,a novel adaptive filter based on surface fitting bidirectional diffusion regularization technology is proposed to detect a week-dim target in such a strong cluttered background.Firstly,the facet model is applied to fit the underlying intensity surface of the image,and then,an average directional derivative gradient operator（ADDG） is designed to describe the multi-degree multi-orientation gradient character of the image.Combining with the ADDG operator,a novel regularizing bidirectional diffusion filter for background suppression is developed.Compared with traditional background suppression algorithms,our method can switch adaptively between forward（background suppression） and backward（targets enhancement） diffusion processes according to the character of the target and background to enhance the signal of interest targets and remove clutter simultaneously.Experimental results show that this method can provide good filtering performance with the advantages of its logical structure simple and easy to implemente in a real-time system.

关 键 词：图像处理 红外弱小目标 Facet小面模型 双向扩散滤波 信号检测 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]