Hierarchical Algorithms for the Classification of Remotely Sensed Multi-Spectral Images
Summary :
Classification algorithms with hierarchical structure are quite effective for the classification of remotely sensed multi-spectral images because the data are vast in volume and have redundancy in spatial, spectral and/or, in some sense, temporal structure. The algorithms bring us high speed and high accuracy in the classification. A couple of hierarchical algorithms developed by the authors in spectral and spatial meaning are described with experimental results.
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- IEICE TRANSACTIONS on Communications Vol.E74-B No.2 pp.295-301
- Publication Date
- 1991/02/25
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- INVITED PAPER
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Sadao FUJIMURA, Hiroshi HANAIZUMI, "Hierarchical Algorithms for the Classification of Remotely Sensed Multi-Spectral Images" in IEICE TRANSACTIONS on Communications,
vol. E74-B, no. 2, pp. 295-301, February 1991, doi: .
Abstract: Classification algorithms with hierarchical structure are quite effective for the classification of remotely sensed multi-spectral images because the data are vast in volume and have redundancy in spatial, spectral and/or, in some sense, temporal structure. The algorithms bring us high speed and high accuracy in the classification. A couple of hierarchical algorithms developed by the authors in spectral and spatial meaning are described with experimental results.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e74-b_2_295/_p
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@ARTICLE{e74-b_2_295,
author={Sadao FUJIMURA, Hiroshi HANAIZUMI, },
journal={IEICE TRANSACTIONS on Communications},
title={Hierarchical Algorithms for the Classification of Remotely Sensed Multi-Spectral Images},
year={1991},
volume={E74-B},
number={2},
pages={295-301},
abstract={Classification algorithms with hierarchical structure are quite effective for the classification of remotely sensed multi-spectral images because the data are vast in volume and have redundancy in spatial, spectral and/or, in some sense, temporal structure. The algorithms bring us high speed and high accuracy in the classification. A couple of hierarchical algorithms developed by the authors in spectral and spatial meaning are described with experimental results.},
keywords={},
doi={},
ISSN={},
month={February},}
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TY - JOUR
TI - Hierarchical Algorithms for the Classification of Remotely Sensed Multi-Spectral Images
T2 - IEICE TRANSACTIONS on Communications
SP - 295
EP - 301
AU - Sadao FUJIMURA
AU - Hiroshi HANAIZUMI
PY - 1991
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E74-B
IS - 2
JA - IEICE TRANSACTIONS on Communications
Y1 - February 1991
AB - Classification algorithms with hierarchical structure are quite effective for the classification of remotely sensed multi-spectral images because the data are vast in volume and have redundancy in spatial, spectral and/or, in some sense, temporal structure. The algorithms bring us high speed and high accuracy in the classification. A couple of hierarchical algorithms developed by the authors in spectral and spatial meaning are described with experimental results.
ER -
English
