Tuning bidirectional feature fusion for hyperspectral classification under 32% band corruption: a threshold audit
PDF

Keywords

hyperspectral classification
bidirectional feature fusion
band corruption
paired simulation
reproducibility

Abstract

We evaluated bidirectional feature fusion for hyperspectral classification under 32% band corruption. A deterministic paired simulation generated 48 cases and preserved a boundary-condition stratum. Mean spectral-spatial accuracy changed from 0.476 to 0.525; the paired difference was +0.050 (95% interval +0.048 to +0.052). The result is limited to the stated simulation and is reported with a reproducible result artifact.

PDF

References

Yang, J.-X., Wang, J., Long, Z., Sui, C., & Zhou, J. (2024). Hyperspectral Images Efficient Spatial and Spectral non-Linear Model with Bidirectional Feature Learning. arXiv. https://doi.org/10.48550/arXiv.2412.00283

Madani, H., & McIsaac, K. (2021). Distance Transform-Based Spectral-Spatial Feature Vector for Hyperspectral Image Classification with Stacked Autoencoder. Remote Sensing, 13(9), 1732. https://doi.org/10.3390/rs13091732

Dang, Y., Zhang, X., Zhao, H., & Liu, B. (2024). DCTransformer: A Channel Attention Combined Discrete Cosine Transform to Extract Spatial-Spectral Feature for Hyperspectral Image Classification. Applied Sciences, 14(5), 1701. https://doi.org/10.3390/app14051701

Reddy, T., & Harikiran, J. (2022). A semi-supervised cycle-GAN neural network for hyperspectral image classification with minimum noise fraction. Journal of Spectral Imaging, a2. https://doi.org/10.1255/jsi.2022.a2

Gong, Z., Zhou, X., & Yao, W. (2024). MultiScale spectral-spatial convolutional transformer for hyperspectral image classification. IET Image Processing, 18(13), 4328-4340. https://doi.org/10.1049/ipr2.13254

Zhu, K., Chen, Y., Ghamisi, P., Jia, X., & Benediktsson, J. A. (2019). Deep Convolutional Capsule Network for Hyperspectral Image Spectral and Spectral-Spatial Classification. Remote Sensing, 11(3), 223. https://doi.org/10.3390/rs11030223

Zhao, X. (2024). Joint Spatial-Spectral Convolutional Neural Network Enhanced with Attention Mechanism for Optimized Hyperspectral Image Classification. Applied and Computational Engineering, 115(1), 117-125. https://doi.org/10.54254/2755-2721/2025.18515

Ahmad, M., Khan, A. M., & Hussain, R. (2017). Graph-based spatial-spectral feature learning for hyperspectral image classification. IET Image Processing, 11(12), 1310-1316. https://doi.org/10.1049/iet-ipr.2017.0168

Song, X., & Wang, C. (2022). Hyperspectral remote sensing image classification based on spectral-spatial feature fusion and PSO algorithm. Journal of Physics: Conference Series, 2189(1), 012010. https://doi.org/10.1088/1742-6596/2189/1/012010

Mu, C., Liu, Y., & Liu, Y. (2021). Hyperspectral Image Spectral-Spatial Classification Method Based on Deep Adaptive Feature Fusion. Remote Sensing, 13(4), 746. https://doi.org/10.3390/rs13040746