Estimating the instantaneous frequencies of a multicomponent AM-FM image by bidimensional empirical mode decomposition

I present an overview of AM-FM image presentation techniques. Many nonstationary textures are multi-partite, and may be considered to comprise several locally narrow-band components. The multicomponent AM-FM model is powerful in describing such images. I apply empirical mode decomposition to processing textures, and propose bidimensional empirical mode decomposition (BEMD) followed by a computationally efficient algorithm. I show that the components may be demodulated on a spatially local basis based on BEMD. I use the Burg linear predicting filter to reduce the decomposition error of BEMD. I propose a practical approach, the direct method, for estimating the instantaneous frequencies of each component.