Abstract:

The aim of this talk is to overview hyperspectral unmixing (HU) techniques from a signal processing researcher’s perspective. HU is one of the most prominent research topics in hyperspectral remote sensing. The problem is to identify materials and their corresponding compositions in a captured scene by using the high spectral degrees of freedom of hyperspectral sensors. From a signal processing viewpoint, this is a blind source separation (BSS) problem. We will review how clever insights from remote sensing researchers and recent involvements from other fields, such as signal processing, optimization and machine learning, lead to elegant HU theory and methods – which depart significantly from conventional BSS techniques, and in fact, give new insights to BSS and hot topics such as low-rank matrix models. If time permits, we may also discuss the connections of HU to other areas such as text mining, biomedical imaging and computer vision.

Biography:

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

Dr. Ma is active in the Signal Processing Society. He is currently a Senior Area Editor of IEEE Transactions on Signal Processing and previously served as editors of several journals, e.g., IEEE Signal Processing Magazine as the Lead Guest Editor of a special issue. He is a Member of the Signal Processing Theory and Methods (SPTM) Technical Committee and 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 an IEEE Fellow.