Higher order Teager-Kaiser operators for image analysis: Part I - A monocomponent image demodulation

We present in this paper a new narrowband image demodulation method. Our approach is based on the 2D higher order Teager-Kaiser operators (HOTKO). We show that the introduction of higher orders in the Teager-Kaiser operator, improves a lot the demodulation results, in comparison to the discrete energy separation algorithm (DESA) and the analytic image (AI) method. More precisely, for synthetic images, we show that the approximation errors on both the amplitude and the frequency components are much more lower with our proposed demodulation method than the DESA and the AI method. Moreover, it turns out that for the presented real images, the algorithm is so efficient, especially the amplitude counterpart, that it tracks the most important parts in images, and segments the regions of interest. We show how the algorithm could be used in sonar images for extracting mines´shadows, which is very important for both military and civil applications.