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Two-Dimensional Change Detection Methods Remote Sensing Applications /
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, t...
| Clasificación: | Libro Electrónico |
|---|---|
| Autores principales: | , |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
London :
Springer London : Imprint: Springer,
2012.
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| Edición: | 1st ed. 2012. |
| Colección: | SpringerBriefs in Computer Science,
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| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 001 | 978-1-4471-4255-3 | ||
| 003 | DE-He213 | ||
| 005 | 20220117170645.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 120621s2012 xxk| s |||| 0|eng d | ||
| 020 | |a 9781447142553 |9 978-1-4471-4255-3 | ||
| 024 | 7 | |a 10.1007/978-1-4471-4255-3 |2 doi | |
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| 100 | 1 | |a İlsever, Murat. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Two-Dimensional Change Detection Methods |h [electronic resource] : |b Remote Sensing Applications / |c by Murat İlsever, Cem Ünsalan. |
| 250 | |a 1st ed. 2012. | ||
| 264 | 1 | |a London : |b Springer London : |b Imprint: Springer, |c 2012. | |
| 300 | |a X, 72 p. 48 illus., 22 illus. in color. |b online resource. | ||
| 336 | |a text |b txt |2 rdacontent | ||
| 337 | |a computer |b c |2 rdamedia | ||
| 338 | |a online resource |b cr |2 rdacarrier | ||
| 347 | |a text file |b PDF |2 rda | ||
| 490 | 1 | |a SpringerBriefs in Computer Science, |x 2191-5776 | |
| 505 | 0 | |a Introduction -- Pixel-Based Change Detection Methods -- Transformation-Based Change Detection Methods -- Structure-Based Change Detection Methods -- Fusion of Change Detection Methods -- Experiments -- Final Comments. | |
| 520 | |a 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. | ||
| 650 | 0 | |a Computer vision. | |
| 650 | 0 | |a Pattern recognition systems. | |
| 650 | 1 | 4 | |a Computer Vision. |
| 650 | 2 | 4 | |a Automated Pattern Recognition. |
| 700 | 1 | |a Ünsalan, Cem. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 710 | 2 | |a SpringerLink (Online service) | |
| 773 | 0 | |t Springer Nature eBook | |
| 776 | 0 | 8 | |i Printed edition: |z 9781447142560 |
| 776 | 0 | 8 | |i Printed edition: |z 9781447142546 |
| 830 | 0 | |a SpringerBriefs in Computer Science, |x 2191-5776 | |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-1-4471-4255-3 |z Texto Completo |
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| 950 | |a Computer Science (SpringerNature-11645) | ||
| 950 | |a Computer Science (R0) (SpringerNature-43710) | ||