IEICE TRANSACTIONS on Communications
Use of Multi-Polarimetric Enhanced Images in SIR-C/X-SAR Land-Cover Classification
Summary :
This paper presents a method for land cover classification using the SIR-C/X-SAR imagery based on the maximum likelihood method and the polarimetric filtering. The main feature is to use polarimetric enhanced image information in the pre-processing stage for the classification of SAR imagery. First, polarimetric filtered images are created where a specific target is enhanced versus another, then the image data are incorporated into the feature vector which is essential for the maximum likelihood classification. Specific target classes within the SAR image are categorized according to the maximum likelihood method using the wavelet transform. Addition of polarimetric enhanced image in the preprocessing stage contributes to the increase of classification accuracy. It is shown that the use of polarimetric enhanced images serves efficient classifications of land cover.
- Publication
- IEICE TRANSACTIONS on Communications Vol.E80-B No.11 pp.1696-1702
- Publication Date
- 1997/11/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Category
- Measurement and Metrology
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Takeshi NAGAI, Yoshio YAMAGUCHI, Hiroyoshi YAMADA, "Use of Multi-Polarimetric Enhanced Images in SIR-C/X-SAR Land-Cover Classification" in IEICE TRANSACTIONS on Communications,
vol. E80-B, no. 11, pp. 1696-1702, November 1997, doi: .
Abstract: This paper presents a method for land cover classification using the SIR-C/X-SAR imagery based on the maximum likelihood method and the polarimetric filtering. The main feature is to use polarimetric enhanced image information in the pre-processing stage for the classification of SAR imagery. First, polarimetric filtered images are created where a specific target is enhanced versus another, then the image data are incorporated into the feature vector which is essential for the maximum likelihood classification. Specific target classes within the SAR image are categorized according to the maximum likelihood method using the wavelet transform. Addition of polarimetric enhanced image in the preprocessing stage contributes to the increase of classification accuracy. It is shown that the use of polarimetric enhanced images serves efficient classifications of land cover.
URL: https://global.ieice.org/en_transactions/communications/10.1587/e80-b_11_1696/_p
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@ARTICLE{e80-b_11_1696,
author={Takeshi NAGAI, Yoshio YAMAGUCHI, Hiroyoshi YAMADA, },
journal={IEICE TRANSACTIONS on Communications},
title={Use of Multi-Polarimetric Enhanced Images in SIR-C/X-SAR Land-Cover Classification},
year={1997},
volume={E80-B},
number={11},
pages={1696-1702},
abstract={This paper presents a method for land cover classification using the SIR-C/X-SAR imagery based on the maximum likelihood method and the polarimetric filtering. The main feature is to use polarimetric enhanced image information in the pre-processing stage for the classification of SAR imagery. First, polarimetric filtered images are created where a specific target is enhanced versus another, then the image data are incorporated into the feature vector which is essential for the maximum likelihood classification. Specific target classes within the SAR image are categorized according to the maximum likelihood method using the wavelet transform. Addition of polarimetric enhanced image in the preprocessing stage contributes to the increase of classification accuracy. It is shown that the use of polarimetric enhanced images serves efficient classifications of land cover.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - Use of Multi-Polarimetric Enhanced Images in SIR-C/X-SAR Land-Cover Classification
T2 - IEICE TRANSACTIONS on Communications
SP - 1696
EP - 1702
AU - Takeshi NAGAI
AU - Yoshio YAMAGUCHI
AU - Hiroyoshi YAMADA
PY - 1997
DO -
JO - IEICE TRANSACTIONS on Communications
SN -
VL - E80-B
IS - 11
JA - IEICE TRANSACTIONS on Communications
Y1 - November 1997
AB - This paper presents a method for land cover classification using the SIR-C/X-SAR imagery based on the maximum likelihood method and the polarimetric filtering. The main feature is to use polarimetric enhanced image information in the pre-processing stage for the classification of SAR imagery. First, polarimetric filtered images are created where a specific target is enhanced versus another, then the image data are incorporated into the feature vector which is essential for the maximum likelihood classification. Specific target classes within the SAR image are categorized according to the maximum likelihood method using the wavelet transform. Addition of polarimetric enhanced image in the preprocessing stage contributes to the increase of classification accuracy. It is shown that the use of polarimetric enhanced images serves efficient classifications of land cover.
ER -
English
