21 citations · 50 across the 10 of their papers we have counts for
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Spatial-Spectral Regularized Local Scaling Cut for Dimensionality Reduction in Hyperspectral Image Classification
Ramanarayan Mohanty, S L Happy, Aurobinda Routray
Dimensionality reduction (DR) methods have attracted extensive attention to provide discriminative information and reduce the computational burden of the hyperspectral image (HSI)…
A Semi-supervised Spatial Spectral Regularized Manifold Local Scaling Cut With HGF for Dimensionality Reduction of Hyperspectral Images
Ramanarayan Mohanty, SL Happy, Aurobinda Routray
Hyperspectral images (HSI) contain a wealth of information over hundreds of contiguous spectral bands, making it possible to classify materials through subtle spectral discrepancie…
A Trace Lasso Regularized L1-norm Graph Cut for Highly Correlated Noisy Hyperspectral Image
Ramanarayan Mohanty, S L Happy, Nilesh Suthar +1
This work proposes an adaptive trace lasso regularized L1-norm based graph cut method for dimensionality reduction of Hyperspectral images, called as `Trace Lasso-L1 Graph Cut' (TL…
A Supervised Geometry-Aware Mapping Approach for Classification of Hyperspectral Images
Ramanarayan Mohanty, S L Happy, Aurobinda Routray
The lack of proper class discrimination among the Hyperspectral (HS) data points poses a potential challenge in HS classification. To address this issue, this paper proposes an opt…