Hierarchical homogeneity-based superpixel segmentation: application to hyperspectral image analysis-Reference-Cited by-同舟云学术

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Hierarchical homogeneity-based superpixel segmentation: application to hyperspectral image analysis

Published:2024-08-09 Issue:17 Volume:45 Page:6004-6042
ISSN:0143-1161
Container-title:International Journal of Remote Sensing
language:en
Short-container-title:International Journal of Remote Sensing

Author:

Ayres L. C.¹^ORCID,de Almeida S. J. M.²,Bermudez J. C. M.¹²,Borsoi R. A.³

Affiliation:

1. Department of Electrical Engineering, Federal University of Santa Catarina, Florianópolis, SC, Brazil

2. RS Pelotas, Catholic University of Pelotas, Pelotas, Brazil

3. Centre de Recherche en Automatique de Nancy (CRAN), Université de Lorraine, CNRS, Vandoeuvre-lès-Nancy, France

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/01431161.2024.2384098

Reference83 articles.

1. Dual-Window Superpixel Data Augmentation for Hyperspectral Image Classification

2. SLIC Superpixels Compared to State-of-the-Art Superpixel Methods

3. Watershed Monitoring in Galicia from UAV Multispectral Imagery Using Advanced Texture Methods

4. Deep Learning for Classification of Hyperspectral Data: A Comparative Review

5. A Generalized Multiscale Bundle-Based Hyperspectral Sparse Unmixing Algorithm

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