Fusing spectral feature and local texture feature for small sample hyperspectral remote sensing image classification

Bingchun Li; Dongping Tian; Yali Wang

doi:10.1117/12.3009408

16 October 2023 Fusing spectral feature and local texture feature for small sample hyperspectral remote sensing image classification

Bingchun Li, Dongping Tian, Yali Wang

Author Affiliations +

Proceedings Volume 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023); 128031N (2023) https://doi.org/10.1117/12.3009408
Event: 2023 5th International Conference on Artificial Intelligence and Computer Science (AICS 2023), 2023, Wuhan, China

Abstract

Hyperspectral remote sensing images (HRSI) contain rich spectral information and spatial structure information which can be effectively used to classify ground objects. In this paper, we propose a feature construction method that combines spectral features, Weber Local Descriptor (WLD) texture features and Gabor texture features. To start with, the spectral information of each pixel is extracted as the basic feature of this pixel. Followed by the local WLD texture feature of each pixel is extracted. Considering the limited expression ability of a single local texture feature, hence the Gabor filtering is carried out on each band respectively to form the Gabor feature map. Singular value decomposition (SVD) is adopted in the local neighborhood, and the singular value is used as the Gabor texture feature of the local neighborhood. Finally, the spectral feature, WLD texture feature and Gabor texture feature are integrated together as the final feature of the pixel, and XGBoost classifier is used for training and classification. Conducted experiments validate that the combination of these spectral features has better expression ability and classification performance.

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

Citation Download Citation

Bingchun Li, Dongping Tian, and Yali Wang "Fusing spectral feature and local texture feature for small sample hyperspectral remote sensing image classification", Proc. SPIE 12803, Fifth International Conference on Artificial Intelligence and Computer Science (AICS 2023), 128031N (16 October 2023); https://doi.org/10.1117/12.3009408

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KEYWORDS

Tunable filters

Image filtering

Feature extraction

Hyperspectral imaging

Remote sensing

Image classification

Histograms

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