Two-Dimensional Change Detection Methods
Remote Sensing Applications
Nonfiction, Computers, Advanced Computing, Engineering, Computer Vision, Application Software, Computer Graphics, General Computing
| Author: | Murat İlsever, Cem Ünsalan | ISBN: | 9781447142553 |
| Publisher: | Springer London | Publication: | June 22, 2012 |
| Imprint: | Springer | Language: | English |
| Author: | Murat İlsever, Cem Ünsalan |
| ISBN: | 9781447142553 |
| Publisher: | Springer London |
| Publication: | June 22, 2012 |
| Imprint: | Springer |
| Language: | English |
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 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.
