经验模式分解去斑和顶帽变换在舰船检测预处理中的应用

Application of EMD-based speckle reduction and tophat transform in preprocessing of ship detection

提出了一种基于经验模式分解去斑和顶帽变换背景不均匀的预处理方法.经验模式分解去斑算法先对图像每一列进行经验模式分解得到IMF函数,然后将原信号与第一、二模态相减得到初步处理图像,再对该图像每一行重复该操作从而得到去斑图像,该算法有效地去除斑点噪声;顶帽变换则有效地补偿了海浪带来的局部不均匀的背景亮度,提高了图像的信杂比,有利于目标的检测.仿真结果证明了算法的有效性.

In this paper,a new algorithm is proposed based on the EMD（empirical mode decomposition） speckle reduction and tophat transform.First,we use EMD to every column signal of the image to get the IMF signals,deduce the first and second IMF signals from the original signal to get a coarse-processed image,and then do the same to the row signal of the coarse-processed image.The speckle can be greatly reduced with this algorithm.Furthermore,the local background of non-homogeneity caused by waves is greatly reduced with tophat transform.The signal-to-clutter-rate of the image is greatly enhanced,which is favorable for detection.The simulation results show the effectiveness of the algorithm.