Dr. Wing-Kin (Ken) Ma Presents at SPS German Chapter

IEEE SPS Distinguished Lecturer, Dr. Wing-Kin (Ken) Ma, gave a talk on “Hyperspectral Unmixing in Remote Sensing: Insights and Beyond.” The lecture, which included Machine Learning, was held on 14 June 2018 for the SPS German Chapter at Technischen Universität Darmstadt. The talk was hosted and moderated by Marius Pesavento and Gerald Enzner.

A recording of the event is now available at the SPS Resource Center and free to all SPS members.

Abstract:

Hyperspectral unmixing (HU) is one of the most prominent research topics in hyperspectral imaging in remote sensing. HU aims at identifying the underlying materials and their corresponding compositions in the scene, using the high spectral degrees of freedom of hyperspectral images. Early HU research is based on smart intuitions from remote sensing. Recent involvement from other fields - such as signal processing, optimization, and machine learning - have substantially enriched HU techniques. In this talk, we will review and discuss the key insights of HU from a signal processing perspective, how such insights led to a unique branch of theory and methods for structured matrix factorization, and why HU has strong connections to problems from other areas such as machine learning, data analytics, computer vision, and biomedical imaging. If time permits, we will also have a quick tour on hyperspectral super-resolution, an emerging and fundamentally intriguing topic in which HU also plays a role.

Wing-Kin (Ken) Ma is an Associate Professor with the Department of Electronic Engineering, The Chinese University of Hong Kong (CUHK). His research interests are in signal processing, optimization and communications, with recent activities focused on structured matrix factorization and applications, and MIMO transceiver designs and interference management.

Dr. Ma is an active member of the IEEE Signal Processing Society and served in various editorial capacities for several journals, e.g., Senior Area Editor of IEEE Transactions on Signal Processing and Lead Guest Editor of a special issue on IEEE Signal Processing Magazine. He was a member of the Signal Processing Theory and Methods (SPTM) Technical Committee, and he is currently a member of the Signal Processing for Communications and Networking (SPCOM) Technical Committee. He received Research Excellence Award 2013–2014 by CUHK, the 2015 IEEE Signal Processing Magazine Best Paper Award, and the 2016 IEEE Signal Processing Letters Best Paper Award. His students received ICASSP Best Student Paper Awards in 2011 and 2014. He is a Fellow of the IEEE and is currently an IEEE SPS Distinguished Lecturer.