Introduction To The Monogenic Signal
It provides an introductory resource for researchers in image processing and computer vision, particularly those working with ultrasound imagery, but is incremental as it does not present new research.
This document introduces the monogenic signal, an image analysis methodology introduced in 2001, to address the lack of a single resource explaining its principles, applications, and limitations, focusing on developing intuition rather than mathematical derivations.
The monogenic signal is an image analysis methodology that was introduced by Felsberg and Sommer in 2001 and has been employed for a variety of purposes in image processing and computer vision research. In particular, it has been found to be useful in the analysis of ultrasound imagery in several research scenarios mostly in work done within the BioMedIA lab at Oxford. However, the literature on the monogenic signal can be difficult to penetrate due to the lack of a single resource to explain the various principles from basics. The purpose of this document is therefore to introduce the principles, purpose, applications, and limitations of the methodology. It assumes some background knowledge from the fields of image and signal processing, in particular a good knowledge of Fourier transforms as applied to signals and images. We will not attempt to provide a thorough math- ematical description or derivation of the monogenic signal, but rather focus on developing an intuition for understanding and using the methodology and refer the reader elsewhere for a more mathematical treatment.