Gaussian Scale-Space Theory

  • Jon Sporring
  • Mads Nielsen
  • Luc Florack
  • Peter Johansen

Part of the Computational Imaging and Vision book series (CIVI, volume 8)

Table of contents

  1. Front Matter
    Pages i-xx
  2. Applications

    1. Front Matter
      Pages 1-1
    2. Bart ter Haar Romeny
      Pages 3-19
    3. Wiro J. Niessen, Robert Maas
      Pages 31-42
  3. The Foundation

    1. Front Matter
      Pages 43-43
    2. Joachim Weickert, Seiji Ishikawa, Atsushi Imiya
      Pages 45-59
    3. Luc Florack
      Pages 61-74
    4. Mads Nielsen
      Pages 99-114
    5. Alfons Salden
      Pages 115-128
    6. Kalle Åström, Anders Heyden
      Pages 129-136
  4. The Structure

    1. Front Matter
      Pages 137-137
    2. Peter Johansen
      Pages 139-146
    3. Lewis Griffin
      Pages 165-180
    4. Stiliyan Kalitzin
      Pages 181-189
    5. Ole Fogh Olsen
      Pages 191-200
  5. Non-linear Extensions

    1. Front Matter
      Pages 201-201
    2. Rein van den Boomgaard, Leo Dorst
      Pages 203-220

About this book

Introduction

Gaussian scale-space is one of the best understood multi-resolution techniques available to the computer vision and image analysis community. It is the purpose of this book to guide the reader through some of its main aspects. During an intensive weekend in May 1996 a workshop on Gaussian scale-space theory was held in Copenhagen, which was attended by many of the leading experts in the field. The bulk of this book originates from this workshop. Presently there exist only two books on the subject. In contrast to Lindeberg's monograph (Lindeberg, 1994e) this book collects contributions from several scale­ space researchers, whereas it complements the book edited by ter Haar Romeny (Haar Romeny, 1994) on non-linear techniques by focusing on linear diffusion. This book is divided into four parts. The reader not so familiar with scale-space will find it instructive to first consider some potential applications described in Part 1. Parts II and III both address fundamental aspects of scale-space. Whereas scale is treated as an essentially arbitrary constant in the former, the latter em­ phasizes the deep structure, i.e. the structure that is revealed by varying scale. Finally, Part IV is devoted to non-linear extensions, notably non-linear diffusion techniques and morphological scale-spaces, and their relation to the linear case. The Danish National Science Research Council is gratefully acknowledged for providing financial support for the workshop under grant no. 9502164.

Keywords

Diffusion Stereo algorithms calculus image analysis

Editors and affiliations

  • Jon Sporring
    • 1
  • Mads Nielsen
    • 2
  • Luc Florack
    • 3
  • Peter Johansen
    • 1
  1. 1.DIKU, Department of Computer ScienceUniversity of CopenhagenCopenhagenDenmark
  2. 2.3D-Laboratory, School of DentistryUniversity of CopenhagenCopenhagenDenmark
  3. 3.Department of Computer Science, Faculty of Mathematics and Computer ScienceUniversity of UtrechtUtrechtThe Netherlands

Bibliographic information

  • DOI https://doi.org/10.1007/978-94-015-8802-7
  • Copyright Information Springer Science+Business Media B.V. 1997
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-90-481-4852-3
  • Online ISBN 978-94-015-8802-7
  • Series Print ISSN 1381-6446
  • About this book
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