Hyperspectral image classification based on multi-feature fusion and different dimensionality reduction methods

Linlin Miao; Shiqing Dou; Yong Xu

doi:10.1117/12.2668169

23 February 2023 Hyperspectral image classification based on multi-feature fusion and different dimensionality reduction methods

Linlin Miao, Shiqing Dou, Yong Xu

Author Affiliations +

Proceedings Volume 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022); 1255117 (2023) https://doi.org/10.1117/12.2668169
Event: Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 2022, Changchun, China

Abstract

The rich band information of hyperspectral images provides data support for accurate classification, but the information redundancy also brings bad effects to image classification. In order to improve the classification accuracy, this paper takes Liutang Town of Guilin City, Guangxi Province as the research area, and "OVS-1A/B" hyperspectral image as the data source. Based on two different dimensionality reduction methods, Principal Components Analysis (PCA) and CfsSubsetEval GreedyStepwise (CG), combined with Support Vector Machine (SVM), classifiers are used to classify hyperspectral images based on four multi-feature fusion schemes, and their classification accuracy is compared. The results show that: (1) In the two classification schemes with different dimensionality reduction methods, the classification accuracy of ground objects increases continuously with the increase of the types of fused features. (2) In the same combination scheme, the classification accuracy obtained by CG feature selection is higher than that obtained by PCA feature extraction. (3) The classification accuracy of scheme 4 using CG method for feature selection was the highest, the overall classification accuracy was 97.12%, and the Kappa coefficient was 0.9556.

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Linlin Miao, Shiqing Dou, and Yong Xu "Hyperspectral image classification based on multi-feature fusion and different dimensionality reduction methods", Proc. SPIE 12551, Fourth International Conference on Geoscience and Remote Sensing Mapping (GRSM 2022), 1255117 (23 February 2023); https://doi.org/10.1117/12.2668169

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KEYWORDS

Image classification

Hyperspectral imaging

Principal component analysis

Feature extraction

Feature selection

Feature fusion

Data fusion

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