关键词: 多通道图像, 经验模态分解, 双拉普拉斯算子, 图像分析和处理

Abstract: The existing Empirical Mode Decomposition（EMD） methods usually ignore the correlation of each channel image when decomposing a multi-channel image（e.g. a color image）. To ameliorate, this paper presents a novel EMD method for multi-channel images. It computes the upper and lower envelopes of multi-channel images by an interpolation approach based on bi-Laplacian operator, and sets up a whole stopping criterion of the sifting process to consider the correlation of all channel images. The novel EMD method can decompose a multi-channel image into a finite number of Intrinsic Mode Functions（IMFs） with different scale features and a residue representing the whole change trend of the image. According to the novel EMD method, a suite of challenging application tasks in image analysis and processing can be undertook, such as image sharpening and night image enhancement. Experimental results demonstrateal this method and its applications can generate good results.

Key words: multi-channel images, empirical mode decomposition, bi-Laplacian operator, image analysis and processing