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Object-based hyperspectral image classification (OBHIC) converts the basic unit from ‘pixel’ to ‘object’ by image segmentation, in order to take advantage of the spatial distribution law of geographical substances, as well as increase classification performances. However, it involves the problem of scale selection, i.e. the segmentation parameters are set manually by empirical values. In this paper,...
This paper presents an object-based fusion of hyperspectral data with LIDAR data for efficient classification of urban areas. Image segmentation is performed on the features extracted from hyperspectral data at multiple levels in a hierarchical way for utilizing spatial information at various scales. Additional information on the classes is derived from the LIDAR data to aid in the classification...
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