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• W2901179989 abstract "Not only the urbanization development but also its ecological process lays emphasis on the Impervious Surface Area (ISA) extraction, whereas, the ISA extraction from high-resolution images is challenging for both the phenomenon of the mixed pixels and shadow effects. To solve the problem, a Multi-Source Dictionary Sparse Representation Classification (MSD-SRC) method using WorldView-2 and TerraSAR-X dataset is proposed. First, it uses multi-source data and fuzzy samples by Low Pass Filtering (LPF) to solve the problem of road and building misclassification; second, learning Multi-Source Dictionary for non-shadow and shadow classes, then using discriminative sparse coding method for classification, therefore to reduce shadow effects and improve the ISA extraction accuracy. Experimental results demonstrated the effectiveness of the proposed method." @default.
• W2901179989 created "2018-11-29" @default.
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• W2901179989 date "2018-07-01" @default.
• W2901179989 modified "2023-09-26" @default.
• W2901179989 title "Sparse Representation for Impervious Surface Area Extraction Using Worldview-2 and terrasar-x data" @default.
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• W2901179989 doi "https://doi.org/10.1109/igarss.2018.8517807" @default.
• W2901179989 hasPublicationYear "2018" @default.
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