Image Restoration, Enhancement and Related AlgorithmsMS49

High quality images are important for both visualization and analysis purpose. Image reconstruction, the process to compute high quality images from raw hardware measurements and image enhancement, the process to obtain higher quality images from different low quality images (e.g., noisy, blurred, low resolution) of the same scene/object are important imaging problems. Appropriate modeling and efficient algorithms are substantial in both problems. This 4-session mini-symposium gathers together the latest theoretical and practical development in this broad topic. Three sessions focus on (depending on titles) while one session focuses on enhancing resolution of multi-spectral and high-spectral images.

Sparse-data Based 3D Surface Reconstruction for Cartoon and Map
Xue-Cheng Tai (Hong Kong Baptist University)
Infimal Convolution of Oscillation Total Generalized Variation for the Recovery of images with structured texture
Kristian Bredies (Universität Graz)
A Distributed Dictionary Learning Algorithm and its Applications
Weihong Guo (Case Western Reserve University)
Variational Models for Joint Subsampling and Reconstruction of Turbulence-degraded Images
Chun Pong Lau (The Chinese University of Hong Kong)
Fast multilevel algorithms for nonlinear optimization in image processing
Abdul Jumaat (University of Liverpool)
Variational Phase Retrieval with globally convergent preconditioned Proximal Algorithm
Yifei Lou (University of Texas at Dallas)
A Multigrid Approach for Multi Scale Total Variation Models
Ke Yin (Huazhong Univeristy of Science and Technology)
High-Resolution Fluorescence Microscopy Image Deconvolution
Jing Qin (Montana State University)
Super-Resolution of Multispectral Multiresolution Images
Mário Figueiredo (Instituto de Telecomunicações and IST, University of Lisboa)
The SparseFI Algorithms for Resolution Enhancement of Optical Remote Sensing Images
Claas Grohnfeldt (Technical University of Munich (TUM))
Fusion of Multispectral and Panchromatic Image: a Review of Classical Approaches and New Developments
Andrea Garzelli (University of Siena)
Producible Kernel Hilbert Space and Heaviside Functions in Image Enhancement
Liang-Jian Deng (University of Electronic Science and Technology of China)
Convex Blind Image Deconvolution with Inverse Filtering
Tieyong Zeng (Department of Mathematics, The Chinese University of Hong Kong, Shatin, N.T.)
Phase Retrieval from Local Measurements: Deterministic Measurement Constructions and Efficient Recovery Algorithms
Aditya Viswanathan (University of Michigan - Dearborn)
Ke Chen (University of Liverpool)
Weihong Guo (Case Western Reserve University)
Guohui Song (Clarkson University)
Xue-Cheng Tai (Hong Kong Baptist University)
image deblurring, image enhancement, image fusion, image reconstruction, image super-resolution, nonlinear optimization