Bidimensional empirical mode decomposition method for image processing in sensing system

Abstract

Recent developments in image processing play a significant role in processing the images clearly. Undoubtedly, identifying the target against clutter is another challenging task in Ground Penetrating Radar (GPR) image processing. To successfully distinguish targets from surrounding clutter, a novel Bidimensional Empirical Mode Decomposition (BEMD) system is proposed. The overall process can be broken down into four steps. First, images are decomposed using BEMD arithmetic to extract the Intrinsic Mode Functions (IMFs). Then, these IMFs could be examined using gradual single frequency signals to bring out and highlight the physical meaning of instantaneous amplitudes and instantaneous frequencies. To find the best-fitting hyperbolas, the object position of the vertex is estimated using maximum point estimation method and velocity is estimated using a minimum entropy method. Finally, the location of reflection hyperbolas can be extracted clearly. The simulation and experimental images show the effectiveness of this method in identifying targets.