ItemConference Paper

Comparative Analysis of GANs and Diffusion Models for Hyperspectral Image Classification

Title
Comparative Analysis of GANs and Diffusion Models for Hyperspectral Image Classification
Creator
Mukunthan, K.; Alenchery, Alex Stanley; Sharma, Dinesh; Deepa, B.G.; Loveline Zeema, J.
Description
Hyperspectral imaging, which is obtained across numerous spectral bands, presents difficulties in classification due to its high dimensionality and intricate nature. This study provides a comparison of Generative Adversarial Networks (GANs) and Diffusion models regarding the classification of the Indian Pines, Pavia University, and Salinas Datasets, utilizing Multi-Layer Perceptron and Random Forest classifiers. The findings indicate the GANs combined with Random Forest outperform Diffusion models, attaining accuracies of 88%, 96% and 95% respectively. This approach may not outperform the top models, such as HTD-2D-3D-PCNN, but is simpler in structure and more computational efficient. Key recommendations would be real-time processing, edge device optimization, and applications customized to agriculture and urban planning. The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.
Source
Smart Innovation, Systems and Technologies;Volume;479 SIST;pp.403-414
Date
01-01-2026
Publisher
Springer Science and Business Media Deutschland GmbH
Subject
Computational Complexity; Diffusion Models; Hyperspectral Imaging; Multi-Layers Perceptron; Spectral Analysis; Spectral Overlap
Coverage
Mukunthan K., Department of Computer Science, CHRIST University, Yeshwanthpur, Bangalore, India; Alenchery A.S., Department of Computer Science, CHRIST University, Yeshwanthpur, Bangalore, India; Sharma D., Department of Computer Science, CHRIST University, Yeshwanthpur, Bangalore, India; Deepa B.G., Department of Computer Science, CHRIST University, Yeshwanthpur, Bangalore, India; Loveline Zeema J., Department of Computer Science, CHRIST University, Yeshwanthpur, Bangalore, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 21903018; ISBN: 978-303218973-8;
Format
online
Language
English
Type
Conference paper

Citation

Mukunthan, K.; Alenchery, Alex Stanley; Sharma, Dinesh; Deepa, B.G.; Loveline Zeema, J., “Comparative Analysis of GANs and Diffusion Models for Hyperspectral Image Classification,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/25400.

Output Formats