基于形态学滤波的快速多通道图像EMD

为了提高多通道图像经验模态分解（EMD）方法分解的效率，提出了一种基于形态学滤波的快速多通道图像EMD方法。利用形态学膨胀和腐蚀滤波可以计算图像上下包络这一重要特性，实现了多通道图像EMD的快速计算，形态学滤波窗口大小由各通道图像的平均极值距离确定，将一幅多通道图像自适应分解为若干个尺度从细到粗的内蕴模态函数（IMF）图像和一个体现图像整体变化趋势的余量。大量的实验结果与对比显示，所提方法不但能够加快EMD方法分解的速度，而且也能够有效地对多通道图像进行自适应分解。通过在图像融合和图像水印中的应用及大量的实验比较，说明了所提方法能够方便快捷地投入到具体的图像处理任务中。 

A fast EMD for multi-channel images based on morphological filter

In order to improve the efficiency of the existing multi-channel image Empirical Mode Decomposition (EMD) methods, this paper presents a fast multi-channel image EMD method based on morphological filter. It uses the morphological expansion and erosion filters to compute the upper and lower envelopes of an image, which can accelerate the implementation of EMD for multi-channel images. The size of the morphological filter window is determined by the average extremum distance of each channel image. The proposed EMD method can decompose a multi-channel image adaptively into several Intrinsic Mode Function (IMF) images with scales from fine to coarse, and a residue representing the overall change trend of the image. A number of experimental results and comparisons show that the proposed method can not only accelerate the decomposition of EMD method, but also generate a good multi-scale adaptive decomposition for a multi-channel image. Its applications in image fusion and image watermarking and many experimental comparisons show that the proposed EMD method can be used to solve some specific image processing tasks conveniently and promptly.