Mathematical Methods for Signal and Image Analysis and Representation

A Short Introduction to Diffusion-like Methods.- Adaptive Filtering using Channel Representations.- 3D-Coherence-Enhancing Diffusion Filtering for Matrix Fields.- Structural Adaptive Smoothing: Principles and Applications in Imaging.- SPD Tensors Regularization via Iwasawa Decomposition.- Sparse Representation of Video Data by Adaptive Tetrahedralizations.- Continuous Diffusion Wavelet Transforms and Scale Space over Euclidean Spaces and Noncommutative Lie Groups.- Left Invariant Evolution Equations on Gabor Transforms.- Scale Space Representations Locally Adapted to the Geometry of Base and Target Manifold.- An A Priori Model of Line Propagation.- Local Statistics on Shape Diffeomorphisms using a Depth Potential Function.- Preserving Time Structures while Denoising a Dynamical Image.- Interacting Adaptive Filters for Multiple Objects Detection.- Visual Data Recognition and Modeling based on Local Markovian Models.- Locally Specified Polygonal Markov Fields for Image Segmentation.- Regularization with Approximated L2 Maximum Entropy Method.