Novel Spectral Loss Function for Unsupervised Hyperspectral Image Segmentation.
Ámbar Pérez-GarcíaMercedes Eugenia PaolettiJuan Mario HautJosé Francisco LópezPublished in: IEEE Geosci. Remote. Sens. Lett. (2023)
Keyphrases
- loss function
- hyperspectral
- image segmentation
- hyperspectral images
- remote sensing
- hyperspectral imagery
- hyperspectral remote sensing
- hyperspectral data
- spectral imagery
- multispectral
- normalized cut
- spectral bands
- infrared
- pairwise
- pixel classification
- hyperspectral image classification
- support vector
- spectral resolution
- image data
- target detection
- unsupervised learning
- image analysis
- semi supervised
- markov random field
- graph cuts
- spectral data
- hyperspectral imaging
- region growing
- spatial resolution
- information content
- supervised classification
- multi band
- supervised learning
- remote sensing images
- satellite images
- reflectance spectra
- computer vision
- image processing
- active contours
- reproducing kernel hilbert space
- machine learning
- multispectral images
- segmentation method
- mean shift
- co occurrence
- change detection
- feature space
- feature extraction