Alireza Hosseini
University of Tehran

Abstract: Inverse problems in image processing involve estimating parameters or data from inadequate observations where observations are often noisy and contain incomplete information about the target parameter or data due to physical limitations of the measurement devices. Consequently, solutions to inverse problems are non-unique. As an example, we know that if focus is not adjusted properly during the photography or the object is moving, the resulting image may be blurred. This criteria can be formulated mathematically as a blurring operator (linear or nonlinear) that operates on a clean image and turns it into a blurred image. This process is named image blurring and the inverse problem aiming to restore the clean image from a given blurred image is called deblurring. Various problems in image processing such as denoising, upscaling, deconvolution and MRI restoration problems can be formulated as inverse problems. In this talk, we introduce some inverse problems in image processing and we also explain how these problems may be formulated as convex optimization problems. Finally, some popular numerical algorithms to solve such problems will be discussed.

Wednesday, 17 November (26 Aban), 2021, 12:00

Organized at University of Tehran, College of Science,
Department of Mathematics, Statistics and Computer Science
Online public access via url https://www.skyroom.online/ch/sci-ut/math-lectures