ISL Colloquium

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Denoising as a Building Block for Imaging, Inverse Problems, and Machine Learning

Peyman Milanfar – Principal Scientist / Director, Google Research

Thu, 10-Feb-2022 / 4:00pm / Zoom

Talk

Abstract

Denoising is one of the oldest problems in imaging. In the last decade, the quality of denoising algorithms has reached phenomenal levels – almost as good as we can ever hope. There are thousands of papers on this topic, and their scope is vast and approaches so diverse that putting them in some order (as I will do) is both useful and challenging. I’ll describe what we can say about this general class of operators, and what makes them so special. I will argue that denoising is still important, not simply as a process for removing noise, but especially now as a core engine and building block for much more complex tasks in imaging, inverse problems, and machine learning.

Bio

Peyman is a Principal Scientist / Director at Google Research, where he leads the Computational Imaging team. Prior to this, he was a Professor of Electrical Engineering at UC Santa Cruz from 1999-2014. He was Associate Dean for Research at the School of Engineering from 2010-12. From 2012-2014 he was on leave at Google-x, where he helped develop the imaging pipeline for Google Glass.

One of the technologies Peyman’s team at Google developed is the Super Res Zoom pipeline for the Pixel phones, which includes both multi-frame and single-frame super-resolution (blog). In addition, the Night Sight mode on Pixel uses technology to merge images (whether you zoom or not) for vivid shots in low light, including time-lapse and video astro-photography.

Peyman received his undergraduate education in electrical engineering and mathematics from the University of California, Berkeley, and the MS and PhD degrees in electrical engineering from the Massachusetts Institute of Technology. He holds 19 patents, where several of his academic inventions are commercially licensed. He founded MotionDSP, which was acquired by Cubic Inc. (NYSE:CUB).

Peyman has been keynote speaker at numerous technical conferences including Picture Coding Symposium (PCS), SIAM Imaging Sciences, SPIE, and the International Conference on Multimedia (ICME). Along with his students, he has won several best paper awards (including the 2021 best paper award) from the IEEE Signal Processing Society.

He is a Distinguished Lecturer of the IEEE Signal Processing Society, and a Fellow of the IEEE “for contributions to inverse problems and super-resolution in imaging.”

All his work can be found at milanfar.org