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Two-Dimensional Change Detection Methods : Remote Sensing Applications / by Murat ?lsever, Cem Ünsalan.

Por: Colaborador(es): Tipo de material: TextoTextoSeries SpringerBriefs in Computer ScienceEditor: London : Springer London : Imprint: Springer, 2012Descripción: x, 72 páginas 48 ilustraciones, 22 ilustraciones en color. recurso en líneaTipo de contenido:
  • texto
Tipo de medio:
  • computadora
Tipo de portador:
  • recurso en línea
ISBN:
  • 9781447142553
Formatos físicos adicionales: Edición impresa:: Sin títuloClasificación LoC:
  • TA1637-1638
Recursos en línea:
Contenidos:
Introduction -- Pixel-Based Change Detection Methods -- Transformation-Based Change Detection Methods -- Structure-Based Change Detection Methods -- Fusion of Change Detection Methods -- Experiments -- Final Comments.
Resumen: 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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Springer eBooks

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

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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