© 2012

Two-Dimensional Change Detection Methods

Remote Sensing Applications


Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)

Table of contents

  1. Front Matter
    Pages i-x
  2. Murat İlsever, Cem Ünsalan
    Pages 1-5
  3. Murat İlsever, Cem Ünsalan
    Pages 7-21
  4. Murat İlsever, Cem Ünsalan
    Pages 23-34
  5. Murat İlsever, Cem Ünsalan
    Pages 35-39
  6. Murat İlsever, Cem Ünsalan
    Pages 41-51
  7. Murat İlsever, Cem Ünsalan
    Pages 53-56
  8. Murat İlsever, Cem Ünsalan
    Pages 57-70
  9. Murat İlsever, Cem Ünsalan
    Pages 71-72

About this book


Change detection using remotely sensed images has many applications, such as urban monitoring, land-cover change analysis, and disaster management. This work investigates two-dimensional change detection methods. The existing methods in the literature are grouped into four categories: pixel-based, transformation-based, texture analysis-based, and structure-based. In addition to testing existing methods, four new change detection methods are introduced: fuzzy logic-based, shadow detection-based, local feature-based, and bipartite graph matching-based. The latter two methods form the basis for a structural analysis of change detection. Three thresholding algorithms are compared, and their effects on the performance of change detection methods are measured. These tests on existing and novel change detection methods make use of a total of 35 panchromatic and multi-spectral Ikonos image sets. Quantitative test results and their interpretations are provided.


Change Detection Remote Sensing Satellite Images Urban Monitoring

Authors and affiliations

  1. 1.Department of Computer EngineeringYeditepe UniversityKayisdagiTurkey
  2. 2.Electrical and Electronics EngineeringYeditepe UniversityKayisdagiTurkey

Bibliographic information

  • Book Title Two-Dimensional Change Detection Methods
  • Book Subtitle Remote Sensing Applications
  • Authors Murat İlsever
    Cem Ünsalan
  • Series Title SpringerBriefs in Computer Science
  • DOI
  • Copyright Information Cem Ünsalan 2012
  • Publisher Name Springer, London
  • eBook Packages Computer Science Computer Science (R0)
  • Softcover ISBN 978-1-4471-4254-6
  • eBook ISBN 978-1-4471-4255-3
  • Series ISSN 2191-5768
  • Series E-ISSN 2191-5776
  • Edition Number 1
  • Number of Pages X, 72
  • Number of Illustrations 26 b/w illustrations, 22 illustrations in colour
  • Topics Image Processing and Computer Vision
    Pattern Recognition
  • Buy this book on publisher's site
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