Fast low-rank-matrix-based connection center evolution for large hyperspectral image clustering-Reference-Cited by-同舟云学术

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Fast low-rank-matrix-based connection center evolution for large hyperspectral image clustering

Published:2023-06 Issue: Volume:131 Page:104666
ISSN:1350-4495
Container-title:Infrared Physics & Technology
language:en
Short-container-title:Infrared Physics & Technology

Author:

Zhang Shiyu,Zhu Liangliang,Ji Luyan,Geng Xiurui

Funder

National Key Research and Development Program of China

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Atomic and Molecular Physics, and Optics,Electronic, Optical and Magnetic Materials

Reference50 articles.

1. Hyperspectral image data analysis;Landgrebe;IEEE Signal Process. Mag.,2002

2. Remote Sensing Digital Image Analysis, vol. 3;Richards,1999

3. Hyperspectral image denoising via noise-adjusted iterative low-rank matrix approximation;He;IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.,2015

4. Spectral–spatial sparse subspace clustering for hyperspectral remote sensing images;Zhang;IEEE Trans. Geosci. Remote Sens.,2016

5. Spectral–spatial classification of hyperspectral imagery with cooperative game;Zhao;ISPRS J. Photogramm. Remote Sens.,2018

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