To read this content please select one of the options below:

HSI-GCN: hyperspectral image classification algorithm based on Gabor convolutional networks

Houari Youcef Moudjib (Beihang University, Beijing, China)
Duan Haibin (Beihang University, Beijing, China)
Baochang Zhang (Beihang University, Beijing, China)
Mohammed Salah Ahmed Ghaleb (USTO MB, Oran, Algeria)

World Journal of Engineering

ISSN: 1708-5284

Article publication date: 31 May 2021

Issue publication date: 29 July 2021

135

Abstract

Purpose

Hyperspectral imaging (HSI) systems are becoming potent technologies for computer vision tasks due to the rich information they uncover, where each substance exhibits a distinct spectral distribution. Although the high spectral dimensionality of the data empowers feature learning, the joint spatial–spectral features have not been well explored yet. Gabor convolutional networks (GCNs) incorporate Gabor filters into a deep convolutional neural network (CNN) to extract discriminative features of different orientations and frequencies. To the best if the authors’ knowledge, this paper introduces the exploitation of GCNs for hyperspectral image classification (HSI-GCN) for the first time. HSI-GCN is able to extract deep joint spatial–spectral features more rapidly and accurately despite the shortage of training samples. The authors thoroughly evaluate the effectiveness of used method on different hyperspectral data sets, where promising results and high classification accuracy have been achieved compared to the previously proposed CNN-based and Gabor-based methods.

Design/methodology/approach

The authors have implemented the new algorithm of Gabor convolution network on the hyperspectral images for classification purposes.

Findings

Implementing the new GCN has shown unexpectable results with an excellent classification accuracy.

Originality/value

To the best of the authors’ knowledge, this work is the first one that implements this approach.

Keywords

Acknowledgements

This work was partially supported by the National Natural Science Foundation of China under grant #91648205, the Aeronautical Foundation of China under grant #20185851022 and Shenzhen Science and Technology Program (No. KQTD2016112515134654).

Citation

Youcef Moudjib, H., Haibin, D., Zhang, B. and Ahmed Ghaleb, M.S. (2021), "HSI-GCN: hyperspectral image classification algorithm based on Gabor convolutional networks", World Journal of Engineering, Vol. 18 No. 4, pp. 590-595. https://doi.org/10.1108/WJE-09-2020-0460

Publisher

:

Emerald Publishing Limited

Copyright © 2021, Emerald Publishing Limited

Related articles