HybridSN: Exploring 3-D–2-D CNN Feature Hierarchy for Hyperspectral Image Classification
Indian Institute of Information Technology Allahabad · Indian Institute of Information Technology Sri City · +1 more institution
Abstract
Hyperspectral image (HSI) classification is widely used for the analysis of remotely sensed images. Hyperspectral imagery includes varying bands of images. Convolutional neural network (CNN) is one of the most frequently used deep learning-based methods for visual data processing. The use of CNN for HSI classification is also visible in recent works. These approaches are mostly based on 2-D CNN. On the other hand, the HSI classification performance is highly dependent on both spatial and spectral information. Very few methods have used the 3-D-CNN because of increased computational complexity. This letter proposes a hybrid spectral CNN (HybridSN) for HSI classification. In general, the HybridSN is a…
Citation impact
- FWCI
- 97.86
- Percentile
- 100%
- References
- 47
Authors
4Topics & keywords
- Hyperspectral imaging
- Convolutional neural network
- Computer science
- Artificial intelligence
- Pattern recognition (psychology)
- Feature (linguistics)
- Contextual image classification
- Feature extraction