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http://dx.doi.org/10.7780/kjrs.2011.27.6.717

Efficient Classification of High Resolution Imagery for Urban Area  

Lee, Sang-Hoon (Department of Industrial Engineering, Kyungwon University)
Publication Information
Korean Journal of Remote Sensing / v.27, no.6, 2011 , pp. 717-728 More about this Journal
Abstract
An efficient method for the unsupervised classification of high resolution imagery is suggested in this paper. It employs pixel-linking and merging based on the adjacency graph. The proposed algorithm uses the neighbor lines of 8 directions to include information in spatial proximity. Two approaches are suggested to employ neighbor lines in the linking. One is to compute the dissimilarity measure for the pixel-linking using information from the best lines with the smallest non. The other is to select the best directions for the dissimilarity measure by comparing the non-homogeneity of each line in the same direction of two adjacent pixels. The resultant partition of pixel-linking is segmented and classified by the merging based on the regional and spectral adjacency graphs. This study performed extensive experiments using simulation data and a real high resolution data of IKONOS. The experimental results show that the new approach proposed in this study is quite effective to provide segments of high quality for object-based analysis and proper land-cover map for high resolution imagery of urban area.
Keywords
Image segmentation; Image classification; Unsupervised analysis; Pixel-linking; High resolution imagery; Regional adjacency graph; Spectral adjacency graph;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
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