Hyperspectral image classification using improved multi-scale block local binary pattern and bi-exponential edge-preserving smoother

Hyperspectral image classification using improved multi-scale block local binary pattern and bi-exponential edge-preserving smoother

ABSTRACTIn this paper, a multi-strategy fusion (MSF) framework, based on improved MBLBP and bi-exponential edge-preserving smoother (BEEPS), is proposed for hyperspectral image (HSI) classification. First, MBLBP operator is adopted to characterize the overall structural information of HSI, where the...

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Bibliographic Details
Main Authors: Xiaoqing Wan, Shuanghao Chen
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:European Journal of Remote Sensing
Subjects:
Classification
hyperspectral image
multiple strategy fusion
multi-scale block local binary pattern
edge-preserving filtering
Online Access:https://www.tandfonline.com/doi/10.1080/22797254.2023.2237654

Internet

https://www.tandfonline.com/doi/10.1080/22797254.2023.2237654

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