Mini-symposium (MS)

MS17: Modeling and Numerical Methods for Image Problems

Organizers: Wei Zhu, University of Alabama at Tuscaloosa

Abstract:  In the past three decades, variational and PDE-based models have achieved remarkable progresses in mathematical imaging and have been intensively employed in practical applications such as medical image analysis, remote sensing, and machine vision. Recently, efficient neural network based models were developed to deal with different imaging tasks including image classification, segmentation, recognition, etc. The main goal of this symposium is to bring together researchers interested in the modeling and numerical methods for imaging problems using PDE-based method or deep learning
based method.

Sunday, September 19, 10:30 AM – 12:30 PM

Room: Libry 3033

10:30 – 11:00 Sung Ha Kang, Georgia Institute of Technology, Image decomposition into structure, harmonic and oscillatory components

11:00 – 11:30 Weihong Guo, Case Western Reserve University, A novel regularization based on the error function for sparse recovery

11:30 – 12:00 Xiaojing Ye, Georgia State University, Learnable descent algorithm for nonsmooth nonconvex optimization with applications in image reconstruction

12:00 – 12:30 Wei Zhu, University of Alabama at Tuscaloosa, First-order image restoration models for staircase reduction and contrast preservation