Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/21550
Title: Object-based spatial feature for classification of very high resolution remote sensing images
Authors: Zhang, P
Lv, Z
Shi, W 
Issue Date: 2013
Source: IEEE geoscience and remote sensing letters, 2013, v. 10, no. 6, 6573351, p. 1572-1576
Abstract: This letter presents a novel spatial feature called object correlative index (OCI) to enhance the classification of very high resolution images. This novel method considers the property of an image object based on spectral similarity to construct a useful OCI to describe the spatial information objectively. Compared with the generic features widely used in image classification, the classification approach based on the OCI spatial feature results in higher classification accuracy than those approaches that only consider spectral features or pixelwise spatial features, such as the pixel shape index and mathematical morphology profiles. Experiments are conducted on QuickBird satellite image and aerial photo data, and results confirm that the proposed method is feasible and effective.
Keywords: Classification of very high resolution (VHR) image
Object correlative index (OCI)
Spatial feature
Spectral feature
Publisher: Institute of Electrical and Electronics Engineers
Journal: IEEE geoscience and remote sensing letters 
ISSN: 1545-598X
DOI: 10.1109/LGRS.2013.2262132
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