Structures and irregularities in image processing and analysis

This book explores novel representations and comparison tools for analyzing structures and irregularities in signals and images. In opposition to most methods, the ideas introduced here work at the pixel-level. Structures and irregularities are studied using approaches that stem from discrepancy theory, functional analysis and potential theory, and low-level signal processing. In particular we show that structure enhancing similarity measures or representations have advantages over usual tools for image comparison and analysis.

Autorentext

Jean-Luc received a Master's degree in applied math-computer science from the french INP-ENSEEIHT. During his last year he worked for T-Systems, Darmstadt, Germany, developing artificial intelligence softwares. He then worked for the Fuzzy Logic Lab, Linz, Austria submitting his thesis in 2012. He is now a postdoc in the math department at Drexel.