Hyperspectral image classification Based on weakened Laplacian pyramid and guided filtering-Reference-Cited by-同舟云学术

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Hyperspectral image classification Based on weakened Laplacian pyramid and guided filtering

Published:2023-09-02 Issue:17 Volume:44 Page:5397-5419
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Wang Wuli¹,Wang Ge¹,Jiang Yumeng¹,Guo Wenhui²,Ren Guangbo³,Wang Jianbu³,Wang Yanjiang²

Affiliation:

1. College of Oceanography and Space Informatics, China University of Petroleum (East China), Qingdao, China

2. College of Control Science and Engineering, China University of Petroleum (East China), Qingdao, China

3. Lab of Marine Physics and Remote Sensing, First Institute of Oceanography, Ministry of Natural Resources, Qingdao, China

Funder

Fundamental Research Funds for the Central Universities of china

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Earth and Planetary Sciences

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2023.2249595

Reference50 articles.

1. GreyWolfLSM: an accurate oil spill detection method based on level set method from synthetic aperture radar imagery

2. A New Statistical-Based Kurtosis Wavelet Energy Feature for Texture Recognition of SAR Images

3. A New Region-Based Active Contour Model with Skewness Wavelet Energy for Segmentation of SAR Images

4. Semi-supervised Hyperspectral image classification using spatial-spectral features and superpixel-based sparse codes

5. Improved Manifold Coordinate Representations of Large-Scale Hyperspectral Scenes

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1. Structural graph learning method for hyperspectral band selection;International Journal of Remote Sensing;2024-09-10

2. A fast hypergraph neural network with detail preservation for hyperspectral image classification;International Journal of Remote Sensing;2024-04-26

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