Trilateral Smooth Filtering for Hyperspectral Image Feature Extraction

Chen Zhikun; Jiang Junjun; Zhou Chong; Jiang Xinwei; Fu Shaoyuan; Cai Zhihua

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Trilateral Smooth Filtering for Hyperspectral Image Feature Extraction

机译：三边光滑图像特征提取

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摘要

Traditional bilateral filtering (BF) cannot extract hyperspectral image (HSI) features well when the center pixel of the neighborhood pixel set is a noise point in the process of filtering the HSI. In this letter, a trilateral smooth filtering (TRSF) is presented. The proposed algorithm avoids the above-mentioned limitation problem in the BF algorithm. TRSF is successfully applied to the feature extraction of three actual HSIs. To prove the effectiveness of the proposed algorithm, support vector machines are used to classify the extracted features. Experimental results show that the proposed feature extraction method is simple and effective.

机译：当邻域像素集的中心像素是过滤HSI过程中的噪声点时，传统的双侧滤波（BF）无法提取高光谱图像（HSI）特征。在这封信中，提出了一个三边平滑过滤（TRSF）。所提出的算法避免了BF算法中上述限制问题。 TRSF成功应用于三个实际HSI的特征提取。为了证明所提出的算法的有效性，支持向量机用于对提取的特征进行分类。实验结果表明，所提出的特征提取方法简单有效。

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来源
《IEEE Geoscience and Remote Sensing Letters》 |2019年第5期|781-785|共5页
作者
Chen Zhikun; Jiang Junjun; Zhou Chong; Jiang Xinwei; Fu Shaoyuan; Cai Zhihua;
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作者单位

Qinzhou Univ Coll Resources & Environm Qinzhou 535011 Peoples R China|China Univ Geosci Sch Comp Sci Wuhan 430074 Hubei Peoples R China;

Harbin Inst Technol Sch Comp Sci & Technol Harbin 150001 Heilongjiang Peoples R China;

Hebei GEO Univ Sch Informat Engn Shijiazhuang 050031 Hebei Peoples R China;

China Univ Geosci Sch Comp Sci Wuhan 430074 Hubei Peoples R China;

Qinzhou Univ Coll Resources & Environm Qinzhou 535011 Peoples R China;

Qinzhou Univ Coll Resources & Environm Qinzhou 535011 Peoples R China|China Univ Geosci Sch Comp Sci Wuhan 430074 Hubei Peoples R China;

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正文语种 eng
中图分类
关键词
Bilateral filtering (BF); feature extraction; hyperspectral image (HSI); trilateral smooth;

机译：双侧过滤（BF）;特征提取;高光谱图像（HSI）;三边光滑;

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专利

1. Trilateral Smooth Filtering for Hyperspectral Image Feature Extraction [J] . Chen Zhikun, Jiang Junjun, Zhou Chong, IEEE Geoscience and Remote Sensing Letters . 2019,第5期

机译：三边平滑滤波用于高光谱图像特征提取
2. Feature Extraction of Hyperspectral Images With Image Fusion and Recursive Filtering [J] . IEEE Transactions on Geoscience and Remote Sensing . 2014,第6期

机译：基于图像融合和递归滤波的高光谱图像特征提取
3. Feature extraction method based on spectral dimensional edge preservation filtering for hyperspectral image classification [J] . Li Zhijian, Zhu Qing, Wang Yaonan, International journal of remote sensing . 2020,第1a2期

机译：基于极光图像分类的谱尺寸边缘保存滤波的特征提取方法
4. Sparse and Smooth Feature Extraction for Hyperspectral Imagery [C] . Behnood Rasti, Magnus O. Ulfarsson, Pedram Ghamisi IEEE International Geoscience and Remote Sensing Symposium . 2018

机译：高光谱图像的稀疏和平滑特征提取
5. A neural relevance model for feature extraction from hyperspectral images, and its application in the wavelet domain. [D] . Mendenhall, Michael J. 2006

机译：用于从高光谱图像中提取特征的神经相关模型及其在小波域中的应用。
6. Spectral-Spatial Feature Extraction of Hyperspectral Images Based on Propagation Filter [O] . Zhikun Chen, Junjun Jiang, Xinwei Jiang, 2018

机译：基于传播滤波器的高光谱图像光谱空间特征提取
7. SuperBF: Superpixel-Based Bilateral Filtering Algorithm and Its Application in Feature Extraction of Hyperspectral Images [O] . Zhikun Chen, Junjun Jiang, Chong Zhou, 2019

机译：SuperBF：基于Superpixel的双侧过滤算法及其在高光谱图像特征提取中的应用
8. Neural Relevance Model for Feature Extraction from Hyperspectral Images, and Its Application in the Wavelet Domain [R] . Mendenhall, M. J. 2006

机译：高光谱图像特征提取的神经关联模型及其在小波域中的应用

Trilateral Smooth Filtering for Hyperspectral Image Feature Extraction

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