Enhancing Hyperspectral Image Classification: A Hybrid CNN Approach with Spatial and Channel Attention Mechanisms

Imtiaz Ahmed Butt, Li Bo, Muhammad Hassaan Farooq Butt, Megabiaw Tewodros Tassew, Muhammad Usama Bin Akhtar Khan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

In the domain of hyperspectral imaging classification (HSIC) for remote sensing, recent advancements in deep learning have proven transformative. Convolutional neural networks have demonstrated immense potential in resolving these issues of HSIC, including insufficient labeled data, redundant spatial and spectral features, and overfitting. Traditional convolutional neural networks (CNNs) have effectively extracted spectral and spatial features, but 2D CNNs are limited in spatial modeling, while 3D CNNs alone struggle to distinguish spectral and spatial characteristics. Given that the accuracy of HSIC hinges on both spatial and spectral information, we proposed a hybrid-CNN model designed to mitigate the constraints of 2D and 3D CNNs. Our approach involves leveraging hybrid CNNs with spatial and channel attention (CA) mechanisms to address challenges like overfitting and model complexity. The proposed framework also improves generalization performance compared to 2D or 3D CNNs alone. Experiments were conducted on open datasets from Pavia University, Indian Pines, and Salinas to validate the proposed approach. The results demonstrate the efficacy of the hybrid CNN model with spatial and CA in consistently producing excellent classification results through thorough analyses with different deep-learning models.

Original languageEnglish
Title of host publication2023 20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350318982
DOIs
StatePublished - 2023
Event20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023 - Chengdu, China
Duration: 15 Dec 202317 Dec 2023

Publication series

Name2023 20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023

Conference

Conference20th International Computer Conference on Wavelet Active Media Technology and Information Processing, ICCWAMTIP 2023
Country/TerritoryChina
CityChengdu
Period15/12/2317/12/23

Keywords

  • Channel Attention
  • Classification
  • Convolutional Neural Networks
  • Remote sensing
  • Spectral Spatial

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