基于小波变换和改进Top-Hat滤波的红外小目标检测

提出了一种基于小波变换与改进Top-Hat滤波的有效地红外小目标检测算法。该方法首先对红外图像进行单层小波分解,分别得到近似、水平、垂直和对角四个分量；接着,对近似分量进行改进Top-Hat滤波,并将滤波结果与原近似分量进行差分,得到差分图像,将其再与水平分量进行融合形成新的近似和水平分量。同时将垂直和对角分量的小波系数置零,进行小波重构。最后,为了进一步凸显红外小目标,采用了基于直方图的灰度变换方法对重构图像进行增强。实验结果证明本文所提出的算法能准确地检测出红外小目标,且鲁棒性较好。

Infrared small target detection based on wavelet transform and improved Top-Hat filter

An infrared small target detection algorithm based on wavelet transform and improved Top-Hat filter is proposed.Firstly,the images were decomposed by the single level wavelet transform to obtain four sub-band wavelet coefficients represented as approximate,horizontal,vertical and diagonal respectively.And then the approximate sub-band was filtered by the improved Top-Hat method,and the difference image was obtained through the difference of filtering results and original approximate sub-band.The filtered approximate sub-band was fused with the horizontal sub-band to obtain new approximate sub-band and horizontal sub-band.The coefficients of vertical sub-band and diagonal sub-band were set to zeros simultaneously.Afterwards,the wavelet transform was reconstructed.To make the targets more prominent,the reconstructed image was enhanced by the grey transformation based on histogram.The experimental results indicate that this method can accurately detect the infrared small target and has good robustness.