中文摘要：

提出了一种将剪切波变换与贝叶斯统计机理相结合的背景抑制新方法来解决红外搜索跟踪系统探测复杂空中和地面背景杂波中的弱小目标这一难题.根据红外图像中目标和背景杂波的不同分布特性,首先,采用剪切波变换对原始红外图像进行多尺度和多方向分解,获得原始图像的多尺度和方向细节特征,然后,通过应用高斯尺度混合模型进行处理,从而将红外图像中弱小目标和背景杂波分离,达到抑制背景的目的,最后采用经典的自适应阈值分割技术得到目标图像,最终实现目标检测.与二维最小均方误差滤波方法相比较,几组实验结果显示,对弱小目标复杂背景具有较好的抑制效果.

英文摘要：

A new background suppression method based on combined shearlet transform and Bayesian mechanism was proposed to solve the problem which is dim and small target detection contained complex sky clouds and ground background clutter for infrared search and tracking system.Firstly,according to difference of distributed charateristiscs between target and background clutter,in infrared image.the shearlet transform was adopted to decompose the origimal infrared image into multi-scale and multi-direction,which extracts multi-scale and multi-direction detail features of origimal image.Then,Gaussian scale mixture（GSM） model was introduced to separate dim,small target and background clutter from infrared image for suppression background.Finally,target image was obtained by using classical adaptive thresholding segmentation technique and target detection implemented.When compared with two dimensional least mean square（TDLMS） method,several groups of experimental results demonstrate that the proposed method can suppress complicated background in dim small target image effectively.