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A split-and-merge approach for hyperspectral band selection

Rashwan, Shaheera and Dobigeon, Nicolas A split-and-merge approach for hyperspectral band selection. (2017) IEEE Geoscience and Remote Sensing Letters, 14 (8). 1378-1382. ISSN 1545-598X

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Official URL: https://ieeexplore.ieee.org/document/7967677/


The problem of band selection (BS) is of great importance to handle the curse of dimensionality for hyperspectral image (HSI) applications (e.g., classification). This letter proposes an unsupervised BS approach based on a split-and-merge concept. This new approach provides relevant spectral sub-bands by splitting the adjacent bands without violating the physical meaning of the spectral data. Next, it merges highly correlated bands and sub-bands to reduce the dimensionality of the HSI. Experiments on three public data sets and comparison with state-of-the-art approaches show the efficiency of the proposed approach.

Item Type:Article
HAL Id:hal-01887849
Audience (journal):International peer-reviewed journal
Uncontrolled Keywords:
Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
Université de Toulouse > Université Toulouse - Jean Jaurès - UT2J (FRANCE)
Université de Toulouse > Université Toulouse 1 Capitole - UT1 (FRANCE)
Other partners > Mubarak City for Science and Technology (EGYPT)
Laboratory name:
Deposited On:11 Sep 2018 14:54

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