2017/03/27 by Christopher P. Bridge, Bridge, Christopher P. · 1 voice
Biochemistry, Genetics and Molecular Biology · Computer Science · Physics and Astronomy · #Cell Image Analysis Techniques #Computational Physics and Python Applications #Computer Vision and Pattern Recognition (cs.CV) #Experimental and Theoretical Physics Studies #FOS: Computer and information sciences #cs.CV
paper · pdf · doi:10.48550/arxiv.1703.09199
arxiv created 2017/03/27 · openalex publication_date 2017/03/27 · arxiv published 2017/03/27 · arxiv updated 2017/03/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.