Research on classification of hyperspectral image based on improved pixel-level and super-pixel-level feature fusion

Xuan Chen

doi:10.1117/12.3007990

14 November 2023 Research on classification of hyperspectral image based on improved pixel-level and super-pixel-level feature fusion

Xuan Chen

Author Affiliations +

Proceedings Volume 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023); 129340R (2023) https://doi.org/10.1117/12.3007990
Event: 2023 3rd International Conference on Computer Graphics, Image and Virtualization (ICCGIV 2023), 2023, Nanjing, China

Abstract

Currently, deep learning has been widely used in the field of hyperspectral image classification, in which hyperspectral image classification methods based on pixel-level and super-pixel-level feature fusion combine the respective advantages of convolutional neural networks and graph convolutional neural networks to achieve better classification results. In this method super pixel-level graph neural network uses linear discriminant analysis to downscale hyperspectral remote sensing images, however, linear discriminant analysis as a supervised linear method cannot downscale the nonlinear hyperspectral data well. To solve this problem, we implemented a hyperspectral image classification method based on kernel principal component analysis for hyper-pixel-level graph neural networks. In general, principal component analysis is applicable to linear dimensionality reduction of data, while kernel principal component analysis can achieve nonlinear dimensionality reduction of data for processing linearly indistinguishable data sets. Extensive experiments on both datasets show that the improved method in this paper is competitive compared to other mainstream methods.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Xuan Chen "Research on classification of hyperspectral image based on improved pixel-level and super-pixel-level feature fusion", Proc. SPIE 12934, Third International Conference on Computer Graphics, Image, and Virtualization (ICCGIV 2023), 129340R (14 November 2023); https://doi.org/10.1117/12.3007990

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KEYWORDS

Hyperspectral imaging

Image classification

Principal component analysis

Remote sensing

Neural networks

Feature extraction

Image segmentation

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