Unsupervised Classification Method for Polarimetric Synthetic Aperture Radar Imagery Based on Yamaguchi Four-Component Decomposition Model

المؤلفون المشاركون

Sun, Sheng
Liu, Renfeng
Wen, Wen

المصدر

Journal of Electrical and Computer Engineering

العدد

المجلد 2015، العدد 2015 (31 ديسمبر/كانون الأول 2015)، ص ص. 1-6، 6ص.

الناشر

Hindawi Publishing Corporation

تاريخ النشر

2015-06-03

دولة النشر

مصر

عدد الصفحات

6

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

For improving the accuracy of unsupervised classification based on scattering models, the four-component Yamaguchi model is introduced, which is an improved version of the best-known three-component Freeman model.

Therewith, the four-component model is combined with the Wishart distance model.

The new proposed algorithm of clustering is rolled out thereafter and the procedure of this new method is listed.

In experiments, seven areas of various homogeneities are singled out from the Flevoland sample image in AIRSAR dataset.

Qualitative and quantitative experiments are performed for a comparative study.

It can be easily seen that the resolution and details are remarkably upgraded by the new proposed method.

The accuracy of classification in homogeneous areas has also increased significantly by adopting the new iterative algorithm.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Sun, Sheng& Liu, Renfeng& Wen, Wen. 2015. Unsupervised Classification Method for Polarimetric Synthetic Aperture Radar Imagery Based on Yamaguchi Four-Component Decomposition Model. Journal of Electrical and Computer Engineering،Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1068137

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Sun, Sheng…[et al.]. Unsupervised Classification Method for Polarimetric Synthetic Aperture Radar Imagery Based on Yamaguchi Four-Component Decomposition Model. Journal of Electrical and Computer Engineering No. 2015 (2015), pp.1-6.
https://search.emarefa.net/detail/BIM-1068137

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Sun, Sheng& Liu, Renfeng& Wen, Wen. Unsupervised Classification Method for Polarimetric Synthetic Aperture Radar Imagery Based on Yamaguchi Four-Component Decomposition Model. Journal of Electrical and Computer Engineering. 2015. Vol. 2015, no. 2015, pp.1-6.
https://search.emarefa.net/detail/BIM-1068137

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references

رقم السجل

BIM-1068137