基于对偶树复小波变换的红外弱小目标背景抑制

为解决结构化背景的抑制,利用对偶树复小波良好的方向选择性、平移不变性和可精确重构的特点,提出了一种基于对偶树复小波变换的红外弱小目标背景抑制方法.首先利用对偶树复小波变换对图像进行分解提取多尺度细节特征,然后采用最大中值滤波对各分解层的小波系数进行非线性地调整来改变目标特征的强度,重构获得估计的背景图像,最终从原图中减去所估计的背景图像实现背景抑制.基于真实的红外图像序列进行实验.结果表明：与二维最小均方误差法相比,该方法从主观视觉和数值指标都具有良好的抑制效果.

Dual-tree Complex Wavelet Transform for Infrared Dim Target Background Suppression

In order to solve the structured background suppression which is a difficult problem for infrared dim target detection technique,a method of infrared dim target background suppression based on DT-CWT is presented,considering the shift invariance,directional selectivity and perfect reconstruction of dual-tree complex wavelet transform (DT-CWT),Firstly,the image is decomposed by DT-CWT  to extract the multi-scale detail characteristics,then wavelet coefficients of each decomposed level is adjusted nonlinear with a Max-Median filter to change the target strength,and the estimated background image is obtained by wavelet reconstruction.The result image is obtained by subtracting the background image from the original image.Based on the real IR image sequences,the experimental results demonstrate that compared with the two-dimensional least mean square error method,the presented method has good effects both in the subjective vision and numerical indices.