A joint 2D AM-FM estimation based on higher order Teager-Kaiser energy operators

In this work, an image demodulation algorithm based on two-dimensional higher order Teager-Kaiser (TK) operators is presented. We show quantitatively and qualitatively that the introduction of higher orders in TK operator improves amplitude modulation (AM) and frequency modulation (FM) estimation results, compared to classical approaches such as the Discrete Energy Separation Algorithm (DESA) or the Analytic Signal (AS) method. Indeed, for a wide class of images, obtained demodulation errors for both the amplitude and frequency are numerically lower than the obtained ones with the DESA and AS method. The proposed method is illustrated on both synthetic and real images. Moreover, it turns out for some real images that the algorithm is very efficient in the sense that it tracks the most significant part in images and segments regions of interests, particularly, the AM counterpart. Finally, an application of our approach to the segmentation of mines' shadows in Sonar images is presented. This is very important for both civil and military applications.