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REMOTE SENSING FOR LAND & RESOURCES    2017, Vol. 29 Issue (4) : 106-113     DOI: 10.6046/gtzyyg.2017.04.16
Heuristics optimized segmentation of agricultural area for high resolution remote sensing image
SU Tengfei, ZHANG Shengwei, LI Hongyu
College of Water Conservancy and Civil Engineering, Inner Mongolia Agricultural University, Hohot 010018, China
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Many mainstream segmentation algorithms for high resolution remote sensing image (HRI)rarely consider the segmentation quality in their region merging process. In order to solve this problem, this paper proposed a strategy to optimize heuristics with the purpose of enhancing segmentation accuracy of HRI captured over agricultural areas. Intra- and inter- region homogeneity models were firstly proposed, with the former constructed upon within-region spectral variance, and the latter considering edge strength extracted from multi-spectral and vegetation information. The criterion of the proposed heuristics was then constructed by combining the intra- and inter- region homogeneity. The new criterion enables the merging process to take into account the segmentation quality, thus constraining over- and under- segmentation errors effectively. Two scenes of HRI acquired over agricultural areas were utilized for validation experiment, and the performance of the proposed method was compared with other two newly proposed methods. By analyzing the quantitative evaluation of the segmentation results, it is found that the proposed method can remarkably improve the segmentation accuracy of HRI in agricultural landscape.

Keywords geological hazard body      change detection      estimation of variable quantity     
:  TP751  
Issue Date: 04 December 2017
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HE Chao. Heuristics optimized segmentation of agricultural area for high resolution remote sensing image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(4): 106-113.
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