Image segmentation algorithms for land categorization
dc.citation.epage | 342 | en_US |
dc.citation.spage | 317 | en_US |
dc.contributor.author | Aksoy, Selim | en_US |
dc.contributor.author | Tilton, J. C. | en_US |
dc.contributor.author | Tarabalka, Y. | en_US |
dc.contributor.editor | Thenkabail, P. S. | |
dc.date.accessioned | 2019-04-30T12:45:41Z | |
dc.date.available | 2019-04-30T12:45:41Z | |
dc.date.issued | 2015 | en_US |
dc.department | Department of Computer Engineering | en_US |
dc.description | Chapter 16 | |
dc.description.abstract | Image segmentation is the partitioning of an image into related meaningful sections or regions. Segmentation is the key ¦rst step for a number of image analysis approaches. Ÿe nature and quality of the image segmentation result is a critical factor in determining the level of performance of these image analysis approaches. It is expected that an appropriately designed image segmentation approach will provide a better understanding of a landscape and/or signi¦cantly increase the accuracy of a landscape classi¦cation. An image can be partitioned in several ways, based on numerous criteria. Whether or not a particular image partitioning is useful depends on the goal of the image analysis application that is fed by the image segmentation result. | en_US |
dc.identifier.isbn | 9781482217865 | en_US |
dc.identifier.uri | http://hdl.handle.net/11693/51044 | en_US |
dc.language.iso | English | en_US |
dc.publisher | Taylor & Francis | en_US |
dc.relation.ispartof | Remote sensing Handbook V.1 Remotely sensed data characterization, classification, and accuracies | en_US |
dc.title | Image segmentation algorithms for land categorization | en_US |
dc.type | Book Chapter | en_US |
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