基于Contourlet变换的红外弱小目标检测方法

介绍了存在背景干扰和噪声情况下的红外图像中弱小目标的检测问题，提出一种基于Contourlet变换的检测算法。首先对图像进行Contourlet变换，利用Contourlet分解后子图像的特性抑制背景和去噪声，最终实现对目标的检测。通过在含有随机目标的红外序列图像中的实验，并与小波变换进行比较，证明了算法的有效性。

Method of infrared dim targets detection based on Contourlet transform

The problem of detecting dim moving targets in infrared image sequences that also contain moving nuisance objects and background noise is addressed in this paper. A new dim target detection approach based on Contourlet transform is put forward. According to the features of the decomposing images after Contourlet transform, the background clutter and noise are eliminated and the final detecting of the target is realized. Comparing to wavelet transform, the effectiveness of this new method is demonstrated by applying the resulting algorithm to infrared images containing opportunity targets.