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Talk on Noise in imaging: focus on correlation and nonlinearity
April 16 @ 2:00 AM - 5:00 PM IST
A two-part talk on
“Noise in imaging: focus on correlation and nonlinearity”
by
Professor Alessandro Foi*, Tampere University (TAU), Finland
(* of the BM3D fame, among other things)
on April 16, 2025 (Wednesday)
from 2 PM to 5.30 PM (coffee break at 3.30 PM)
Venue: Multimedia Classroom (MMCR), EE Department
Abstract:
Understanding and characterizing noise is a foundational part of the design and analysis of an imaging system, and it is also essential for the development of the corresponding image processing modules. In this talk we consider broad classes of heteroskedastic image observations and specifically focus on the noise correlation, the noise anisotropy, and on the nonlinear effects that can arise when dealing with capture at low signal-to-noise ratio or when maximizing the coverage of a narrow dynamic range. We demonstrate possibly unexpected and perhaps counter-intuitive phenomena which, unless suitably modeled and accounted for, can significantly disrupt the noise analysis and other operations in an image processing pipeline.
Understanding and characterizing noise is a foundational part of the design and analysis of an imaging system, and it is also essential for the development of the corresponding image processing modules. In this talk we consider broad classes of heteroskedastic image observations and specifically focus on the noise correlation, the noise anisotropy, and on the nonlinear effects that can arise when dealing with capture at low signal-to-noise ratio or when maximizing the coverage of a narrow dynamic range. We demonstrate possibly unexpected and perhaps counter-intuitive phenomena which, unless suitably modeled and accounted for, can significantly disrupt the noise analysis and other operations in an image processing pipeline.
The talk is divided into two parts.
In the first part, I will introduce concrete examples and the relevant mathematical models of noise found in various imaging and image processing systems used in biomedical, defense, security, as well as consumer applications, including x-ray tomography, infrared thermography, confocal fluorescence microscopy, and on-demand video streaming.
In the second part, I will discuss the spectral distortion that takes place when nonlinear transformations are applied to correlated noise. In particular, I will consider the case of clipping (e.g., saturation, over-exposure, under-exposure) and the application of variance-stabilizing transformations.
Biography of the speaker:
Alessandro Foi is a Professor of Signal Processing at Tampere University (TAU), Finland. He leads the Signal and Image Restoration group and he is the director of TAU 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.
He 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. 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.
Host faculty: Prof. Soma Biswas (EE) and Prof. Chandra Sekhar Seelamantula (EE)