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Two-Dimensional Change Detection Methods: Remote Sensing Applications: SpringerBriefs in Computer Science

Autor Murat İlsever, Cem Ünsalan
en Limba Engleză Paperback – 24 iun 2012
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.
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Specificații

ISBN-13: 9781447142546
ISBN-10: 1447142543
Pagini: 82
Ilustrații: X, 72 p. 48 illus., 22 illus. in color.
Dimensiuni: 155 x 235 x 20 mm
Greutate: 0.14 kg
Ediția:2012
Editura: SPRINGER LONDON
Colecția Springer
Seria SpringerBriefs in Computer Science

Locul publicării:London, United Kingdom

Public țintă

Research

Cuprins

Introduction.- Pixel-Based Change Detection Methods.- Transformation-Based Change Detection Methods.- Structure-Based Change Detection Methods.- Fusion of Change Detection Methods.- Experiments.- Final Comments.

Textul de pe ultima copertă

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.

Caracteristici

Discusses change detection methods for remote sensing applications Summarizes well-known methods in the literature Proposes novel methods to solve the problem Includes supplementary material: sn.pub/extras Includes supplementary material: sn.pub/extras