Signal Processing and Education Societies

Speaker: Prof. Alessandro Foi, IEEE SPS Distinguished Lecturer

School: Tampere University, Finland

Understanding and characterizing noise is fundamental to the design and analysis of imaging systems and to the development of their image-processing components. This lecture examines broad classes of heteroskedastic image observations, with emphasis on noise correlation, noise anisotropy, and nonlinear effects arising from low signal-to-noise ratio (SNR), limited bit depth, and the need to maximize coverage of a narrow dynamic range. Special attention is given to the largely overlooked case of spatially correlated heteroskedastic noise subject to clipping, including extreme underexposure and overexposure. We highlight several unexpected and counterintuitive phenomena that can significantly compromise noise analysis and other stages of an image-processing pipeline unless they are properly modeled and addressed. Examples are drawn from imaging and image-processing systems used in biomedical, defense, security, and consumer applications. These include X-ray tomography, infrared thermography, video streaming, confocal fluorescence microscopy, as well as scanning electron microscopy. In addition to conventional random noise in extremely low SNR conditions, the models presented can describe various forms of structured noise and artifacts, including streak and ring artifacts in tomography, cutting artifacts introduced during volume sectioning with a diamond microtome or an ion beam, and fixed-pattern noise.

Prof. Alessandro Foi

Alessandro Foi received the M.Sc. degree in Mathematics from the Università degli Studi di Milano, Italy, in 2001, the Ph.D. degree in Mathematics from the Politecnico di Milano in 2005, and the D.Sc.Tech. degree in Signal Processing from Tampere University of Technology, Finland, in 2007. He is a Professor of Signal Processing at Tampere University, Finland, and the Director of Tampere University Imaging Research Platform. He is also the CTO of Noiseless Imaging, a company specialized in noise-removal, restoration, and enhancement technology for the imaging industry.

His research interests include mathematical and statistical methods for signal processing, functional and harmonic analysis, and computational modeling of the human visual system. His work focuses on spatially adaptive algorithms for the restoration and enhancement of digital images, on noise modeling for imaging devices, and on the optimal design of statistical transformations for the stabilization, normalization, and analysis of random data. He is a Fellow of the IEEE for his contributions to image restoration and noise modeling. He was the Editor-in-Chief of the IEEE Transactions on Image Processing from 2021 to 2023. He previously served as a Senior Area Editor for the IEEE Transactions on Computational Imaging and as an Associate Editor for the IEEE Transactions on Image Processing, the SIAM Journal on Imaging Sciences, and the IEEE Transactions on Computational Imaging. He was the Lead Technical Program Chair of the 2026 IEEE International Conference on Image Processing.

Location:  Boston University, 8 St. Mary’s Street, Boston, Massachusetts.  Building: ECE Dept.  Room Number: Room PHO339

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