Research Papers

Adaptive regional feature extraction for very high spatial resolution image classification

[+] Author Affiliations
Leiguang Wang

Southwest Forestry University, School of Forestry, Panlong District, Kunming, China 650224

Qinling Dai

Southwest Forestry University, School of Materials Engineering, Panlong District, Kunming, China 650224

Liang Hong

Yunnan Normal University, College of Tourism and Geography Science, Chengong District, Kunming, China 650500

Guoying Liu

Anyang Normal University, School of Computer and Information Engineering, Huanghe Road, Anyang, China 455002

J. Appl. Remote Sens. 6(1), 063506 (Mar 07, 2012). doi:10.1117/1.JRS.6.063506
History: Received July 25, 2011; Revised November 24, 2011; Accepted December 2, 2011
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Abstract.  An object-oriented, multiscale feature extraction approach is proposed for the land-cover classification of high spatial resolution images. The approach provides more discriminative features by considering the spatial context information from different segmentation levels. It consists of three successive substeps: segmentation by mean-shift algorithm, an iteratively merging process controlled by merging cost function and range-of-scale parameter, and feature extraction from linked multilevel image partitions. The mean-shift method is to get boundary-preserved and spectrally homogeneous over-segmentation regions. Then, a family of nested image partitions is constructed by a merging procedure. Meanwhile, every region of the finest scale is linked to image objects of its superlevels. Finally, every region in the finest scale is treated as a basic analysis unit, and the feature vectors are created by stacking statistics from the region and their superlevels. A support vector machine is used as a classifier and the method on two widely used high spatial resolution data sets over Pavia City, Italy, are evaluated. Compared with results reported in many papers, the result indicates superior accuracy.

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© 2012 Society of Photo-Optical Instrumentation Engineers

Citation

Leiguang Wang ; Qinling Dai ; Liang Hong and Guoying Liu
"Adaptive regional feature extraction for very high spatial resolution image classification", J. Appl. Remote Sens. 6(1), 063506 (Mar 07, 2012). ; http://dx.doi.org/10.1117/1.JRS.6.063506


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