Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 13, Issue 12, Pages 1965-1969Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2016.2619163
Keywords
Change detection; conditional random fields (CRFs); high spatial resolution (HSR); probabilistic ensemble; remote sensing
Categories
Funding
- National Natural Science Foundation of China [41622107, 41371344]
- Natural Science Foundation of Hubei Province [2016-29]
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In this letter, a multifeature probabilistic ensemble conditional random field (MFPECRF) model is proposed to perform the task of change detection for high spatial resolution (HSR) remote sensing imagery. MFPECRF not only considers the spectral feature of single pixels but also the interaction between neighborhood pixels and the structural property of the ground objects in HSR imagery to give a higher detection accuracy than the traditional random field methods, which only utilize spectral and label information. In the unary potential, the spectral and morphological features of the difference image are combined using a probabilistic ensemble strategy, and the pairwise potential considers the contextual information of the observed field. The parameters of MFPECRF are estimated using a piecewise strategy, and the final result is obtained by the use of the loopy belief propagation algorithm. The experimental results of two groups of HSR multispectral images confirm the potential of the proposed method in improving the detection accuracy for HSR imagery.
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