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Descripción
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| Change detection in imagery is quite useful generally but it has particular value in the remote sensing context. The conventional change detection methods based on pixel, which are ap-propriate to the low/middle resolution images, could not model the high-resolution imagery very well. In this case the object-based change detection techniques become effectives. The main ad-vantage of the object-based approaches is that the digital image is no longer considered as a grid of pixels, but as a group of regions, called image objects. In this research, an effective change detec-tion method based on image segmentation is performed. The proposed method involves filtering bands of a multispectral image with a bilateral filter, and obtaining the changed objects by means a method based on a region growing approach. For the analysis of the quality of the resulting seg-mentation, a measure of intrasegment homogeneity (variance indicator) and one of intersegment heterogeneity (Moran index) have been used. The changed segments are placed into the multitem-poral images to identify the nature of change (from-to). In urban expansion areas, the results are promising and show that object-oriented systems facilitate the interpretation of change detection results derived from commercial satellite data. | |
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Internacional
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Si |
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DOI
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Edición del Libro
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1 |
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Editorial del Libro
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Lena Halounova. Czech Technical University in Prague |
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ISBN
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978-80-01-04868-9 |
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Serie
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Título del Libro
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Remote Sensing and Geoinformation not only for Scientific Cooperation |
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Desde página
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239 |
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Hasta página
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246 |