کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4948096 | 1439607 | 2017 | 9 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Class-wise dictionary learning for hyperspectral image classification
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Class-wise dictionary learning for hyperspectral image classification Class-wise dictionary learning for hyperspectral image classification](/preview/png/4948096.png)
چکیده انگلیسی
In order to effectively exploit the intra-class and inter-class structure information, we propose a new class-wise dictionary learning method for hyperspectral image classification. First, we construct two special manifold regularizers to encourage intra-class basis sharing and inter-class basis competition, and the regularizers are incorporated into the objective function to learn a discriminative class-wise dictionary. Then the sparse representations can be obtained via the learned class-wise dictionary under the collaborative representation framework. Finally, we put the sparse representations of the data into the support vector machine (SVM) for training and then apply the SVM classifiers to predict labels for the test set. The experimental results obtained on two hyperspectral datasets demonstrate that the proposed method can obtain higher classification accuracy with much lower computational cost compared with other traditional classifiers.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Neurocomputing - Volume 220, 12 January 2017, Pages 121-129
Journal: Neurocomputing - Volume 220, 12 January 2017, Pages 121-129
نویسندگان
Siyuan Hao, Wei Wang, Yan Yan, Lorenzo Bruzzone,