The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
Kaedah pengelasan tanpa pengawasan baharu dicadangkan untuk imej SAR polarimetrik untuk mengekalkan keselarasan ruang piksel dan tepi pelbagai jenis sasaran secara serentak. Kami menganggap kebolehubahan skala label imej dengan menggabungkan Inhomogeneous Markov Random Field (MRF) dan teorem Bayes. Selepas meminimumkan fungsi tenaga menggunakan algoritma pengembangan berdasarkan Pemotongan Graf, kita boleh mendapatkan keputusan pengelasan yang mengekalkan ketakselanjaran. Menggunakan imej NASA/JPL AIRSAR, kami menunjukkan keberkesanan kaedah yang dicadangkan.
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Salinan
Xing RONG, Weijie ZHANG, Jian YANG, Wen HONG, "A New Approach to Unsupervised Target Classification for Polarimetric SAR Images" in IEICE TRANSACTIONS on Communications,
vol. E91-B, no. 6, pp. 2081-2084, June 2008, doi: 10.1093/ietcom/e91-b.6.2081.
Abstract: A new unsupervised classification method is proposed for polarimetric SAR images to keep the spatial coherence of pixels and edges of different kinds of targets simultaneously. We consider the label scale variability of images by combining Inhomogeneous Markov Random Field (MRF) and Bayes' theorem. After minimizing an energy function using an expansion algorithm based on Graph Cuts, we can obtain classification results that are discontinuity preserving. Using a NASA/JPL AIRSAR image, we demonstrate the effectiveness of the proposed method.
URL: https://global.ieice.org/en_transactions/communications/10.1093/ietcom/e91-b.6.2081/_p
Salinan
@ARTICLE{e91-b_6_2081,
author={Xing RONG, Weijie ZHANG, Jian YANG, Wen HONG, },
journal={IEICE TRANSACTIONS on Communications},
title={A New Approach to Unsupervised Target Classification for Polarimetric SAR Images},
year={2008},
volume={E91-B},
number={6},
pages={2081-2084},
abstract={A new unsupervised classification method is proposed for polarimetric SAR images to keep the spatial coherence of pixels and edges of different kinds of targets simultaneously. We consider the label scale variability of images by combining Inhomogeneous Markov Random Field (MRF) and Bayes' theorem. After minimizing an energy function using an expansion algorithm based on Graph Cuts, we can obtain classification results that are discontinuity preserving. Using a NASA/JPL AIRSAR image, we demonstrate the effectiveness of the proposed method.},
keywords={},
doi={10.1093/ietcom/e91-b.6.2081},
ISSN={1745-1345},
month={June},}
Salinan
TY - JOUR
TI - A New Approach to Unsupervised Target Classification for Polarimetric SAR Images
T2 - IEICE TRANSACTIONS on Communications
SP - 2081
EP - 2084
AU - Xing RONG
AU - Weijie ZHANG
AU - Jian YANG
AU - Wen HONG
PY - 2008
DO - 10.1093/ietcom/e91-b.6.2081
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E91-B
IS - 6
JA - IEICE TRANSACTIONS on Communications
Y1 - June 2008
AB - A new unsupervised classification method is proposed for polarimetric SAR images to keep the spatial coherence of pixels and edges of different kinds of targets simultaneously. We consider the label scale variability of images by combining Inhomogeneous Markov Random Field (MRF) and Bayes' theorem. After minimizing an energy function using an expansion algorithm based on Graph Cuts, we can obtain classification results that are discontinuity preserving. Using a NASA/JPL AIRSAR image, we demonstrate the effectiveness of the proposed method.
ER -