Morphological operation-based bi-dimensional empirical mode decomposition for adaptive texture extraction of images

A new bi-dimensional empirical mode decomposition (EMD) is proposed for sparsely decomposing a textured image into two components, namely, a single intrinsic mode function (IMF) and a residue. The sifting process of this method employs morphological operations to detect the ridges and troughs of images, and uses weighted moving average algorithm to estimate envelopes. The texture of the image is automatically retrieved by extracting the single IMF. The method can solve two key problems, namely, mode mixing and inappropriate interpolation of 2D scattered data. Fast algorithm is also presented for reducing the calculation time to several seconds only. This approach is applied to process simulated and real images.