Fuzzy image segmentation for urban land-cover classification
Lizarazo, Ivan and Barros, Joana (2010) Fuzzy image segmentation for urban land-cover classification. Photogrammetric Engineering and Remote Sensing , pp. 151-162. ISSN 0099-1112.
A main problem of hard image segmentation is that, in complex landscapes, such as urban areas, it is very hard to produce meaningful crisp image-objects. This paper proposes a fuzzy approach for image segmentation aimed to produce fuzzy image-regions expressing degrees of membership of pixels to different target classes. This approach, called Fuzzy Image-Regions Method (FIRME), is a natural way to deal with the inherent ambiguity of remotely sensed images. The FIRME approach comprises three main stages: (a) image segmentation which creates fuzzy image-regions, (b) feature analysis which measures properties of fuzzy image regions, and (c) classification which produces the intended land-cover classes. The FIRME method was evaluated in a land-cover classification experiment using high spectral resolution imagery in an urban zone in Bogota, Colombia. Results suggest that in complex environments, fuzzy image segmentation may be a suitable alternative for GEOBIA as it produces higher thematic accuracy than the hard image segmentation and other traditional classifiers.
|Keyword(s) / Subject(s):||soil survey, areas|
|School:||Birkbeck Schools and Departments > School of Social Sciences, History and Philosophy > Geography, Environment and Development Studies|
|Date Deposited:||31 Mar 2011 15:48|
|Last Modified:||17 Apr 2013 12:20|
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