Optimization techniques in computer vision. Ill-posed problems and regularization
type: Item
instance of: scholarly article
title: Optimization techniques in computer vision. Ill-posed problems and regularization
zbMATH Open document ID: 1362.68003
DOI: 10.1007/978-3-319-46364-3
author: Mongi A. Abidi
author: Andrei V. Gribok
author: Joonki Paik
published in: Advances in Computer Vision and Pattern Recognition
publication date: 2017-01-20T00:00:00Z
review text: Image processing and computer vision provide a large variety of problems where optimization is necessary and there are not many books to address this necessity directly. This volume thoroughly presents several optimization problems and how they are related to image processing and computer vision and many solutions for dealing with such situations. Optimization techniques for image processing target image quantization, image filtering, image reconstruction and others, while for computer vision examples include feature detection, motion estimation or pattern matching. The presentation of the problems is accompanied by illustrating examples. The book contains both a great theoretical background and practical applications and is thus self-contained. It is useful for master and doctoral students, as well as for researchers and practitioners dealing with computer vision and image processing, but also working in mathematical optimization.
reviewed by: Ruxandra Stoean
Mathematics Subject Classification ID: 68-02
Mathematics Subject Classification ID: 68T45
Mathematics Subject Classification ID: 68U10
Mathematics Subject Classification ID: 90C90
zbMATH DE Number: 6676690
zbMATH Keywords: pattern recognition
zbMATH Keywords: computer vision
zbMATH Keywords: image processing
zbMATH Keywords: ill-posed problems
zbMATH Keywords: regularization
zbMATH Keywords: constrained optimization
zbMATH Keywords: unconstrained optimization
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1007/978-3-319-46364-3
OpenAlex ID: W2560316873
description: scientific article; zbMATH DE number 6676690