IMAGE EMPIRICAL MODE DECOMPOSITION: A NEW TOOL FOR IMAGE PROCESSING

Image empirical mode decomposition (IEMD) is an empirical mode decomposition concept used in Hilbert-Huang transform (HHT) expanded into two dimensions for the use on images. IEMD provides a tool for image processing by its special ability to locally separate superposed spatial frequencies. The tendency is that the intrinsic mode functions (IMFs) other than the first are low-frequency images. In this study we give an overview of the state-of-the-art methods to decompose an image into a number of IMFs and a residue image with a minimum number of extrema points, together with the use of the method. Ideas and open problems are presented.