Two-Dimensional Change Detection Methods
İlsever, Murat.
Two-Dimensional Change Detection Methods Remote Sensing Applications / [electronic resource] : by Murat İlsever, Cem Ünsalan. - X, 72 p. 48 illus., 22 illus. in color. online resource. - SpringerBriefs in Computer Science, 2191-5768 . - SpringerBriefs in Computer Science, .
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.
9781447142553
10.1007/978-1-4471-4255-3 doi
Computer science.
Computer vision.
Optical pattern recognition.
Computer Science.
Image Processing and Computer Vision.
Pattern Recognition.
TA1637-1638 TA1637-1638
006.6 006.37
Two-Dimensional Change Detection Methods Remote Sensing Applications / [electronic resource] : by Murat İlsever, Cem Ünsalan. - X, 72 p. 48 illus., 22 illus. in color. online resource. - SpringerBriefs in Computer Science, 2191-5768 . - SpringerBriefs in Computer Science, .
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.
9781447142553
10.1007/978-1-4471-4255-3 doi
Computer science.
Computer vision.
Optical pattern recognition.
Computer Science.
Image Processing and Computer Vision.
Pattern Recognition.
TA1637-1638 TA1637-1638
006.6 006.37