Hyperspectral Image Segmentation
5 papers with code • 0 benchmarks • 1 datasets
Benchmarks
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LIB-HSI
Most implemented papers
Validating Hyperspectral Image Segmentation
Oscared/thesis
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Hyperspectral satellite imaging attracts enormous research attention in the remote sensing community, hence automated approaches for precise segmentation of such imagery are being rapidly developed.
A distribution-dependent Mumford-Shah model for unsupervised hyperspectral image segmentation
We equipped the MS functional with a novel robust distribution-dependent indicator function designed to handle the characteristic challenges of hyperspectral data.
Exploring the Relationship between Center and Neighborhoods: Central Vector oriented Self-Similarity Network for Hyperspectral Image Classification
lms-07/CVSSN
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IEEE Transactions on Circuits and Systems for Video Technology 2022
Specifically, based on two similarity measures, we firstly design an adaptive weight addition based spectral vector self-similarity module (AWA-SVSS) in input space and a Euclidean distance based feature vector self-similarity module (ED-FVSS) in feature space to fully mine the central vector oriented spatial relationships.
Hyperspectral Image Segmentation: A Preliminary Study on the Oral and Dental Spectral Image Database (ODSI-DB)
Visual discrimination of clinical tissue types remains challenging, with traditional RGB imaging providing limited contrast for such tasks.
Adaptive Mask Sampling and Manifold to Euclidean Subspace Learning with Distance Covariance Representation for Hyperspectral Image Classification
lms-07/AMS-M2ESL
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IEEE Transactions on Geoscience and Remote Sensing 2023
Subsequently, based on distance covariance descriptor, a dual channel distance covariance representation (DC-DCR) module is proposed for modeling unified spectral-spatial feature representations and exploring spectral-spatial relationships, especially linear and nonlinear interdependence in spectral domain.
