Signal and Image Processing and Computational Imaging: Algorithms, Theory and associated applications

Professor Steve McLaughlin is Deputy Principal for Research and Impact at Heriot Watt University, with responsibility for implementing the Universities research and innovation strategy. Prior to taking up this role he was Head of the School of Engineering and Physical Sciences at Heriot Watt from 2011-2020. he is a Fellow of the Royal Society of Edinburgh, the Royal Academy of Engineering, the IEEE, the IET and a Fellow of the European Signal Processing Association.

For the last 35 years my research interest has been the study of signals and their interaction with systems. These signals are in general electrical signals, as in communication systems, or imaging systems as in medical or hyperspectral imaging methods, or digitally sampled naturally occurring signals, for example in speech and geophysics. In particular, my focus has been signal processing. Signal Processing is the transformations applied to measurements to maximise their usefulness by an observer or a computer. Typically this is for the purposes of: signal-to-noise enhancement, i.e. optimal extraction of a signal from background noise; detection, i.e. determining if a particular signal is present; parameter estimation, i.e. estimation of the characteristics of a signal or underlying system; classification, i.e. of a signals source or of its nature. These methods coupled with the use of Bayesian statistical methods have enabled the development of signal processing methods that exploit the evidence in the data.