Spectral–Spatial Hyperspectral Image Classification With Edge-Preserving Filtering
University of Iceland · Hunan University
Abstract
The integration of spatial context in the classification of hyperspectral images is known to be an effective way in improving classification accuracy. In this paper, a novel spectral-spatial classification framework based on edge-preserving filtering is proposed. The proposed framework consists of the following three steps. First, the hyperspectral image is classified using a pixelwise classifier, e.g., the support vector machine classifier. Then, the resulting classification map is represented as multiple probability maps, and edge-preserving filtering is conducted on each probability map, with the first principal component or the first three principal components of the hyperspectral image serving as the gray…
Citation impact
- FWCI
- 44.57
- Percentile
- 100%
- References
- 53
Authors
3Topics & keywords
- Hyperspectral imaging
- Artificial intelligence
- Pattern recognition (psychology)
- Spatial contextual awareness
- Principal component analysis
- Contextual image classification
- Computer science
- Pixel