On and Beyond Total Variation Regularization in Imaging - The Role of Space Variance

Explore advanced techniques in image regularization and inverse problems through this virtual seminar talk. Delve into the role of space variance in Total Variation (TV) regularization for imaging applications. Learn how adaptive mathematical modeling incorporating local regularization weighting, variable smoothness, and anisotropy can enhance image reconstruction. Discover the interpretation of these models within the Bayesian framework of Generalized Gaussian Distributions and their combination with maximum likelihood and hierarchical optimization approaches for efficient hyper-parameter estimation. Gain insights into the validation of this combined modeling approach on standard image restoration problems. Presented by Luca Calatroni from Université Côte d'Azur, this talk offers valuable knowledge for researchers and practitioners in the field of imaging and inverse problems.

Seventeenth Imaging & Inverse Problems (IMAGINE) OneWorld SIAM-IS Virtual Seminar Series Talk