Hyperspectral Image Segmentation
5 papers with code • 0 benchmarks • 1 datasets
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LIB-HSI
Latest papers with no code
Hyperspectral Image Segmentation based on Graph Processing over Multilayer Networks
One important task of hyperspectral image (HSI) processing is the extraction of spectral-spatial features.
Sparse Subspace Clustering Friendly Deep Dictionary Learning for Hyperspectral Image Classification
We show that the proposed formulation improves over the state-of-the-art deep learning techniques in hyperspectral image clustering.
Image Processing via Multilayer Graph Spectra
Graph signal processing (GSP) has become an important tool in image processing because of its ability to reveal underlying data structures.
Deep Learning Hyperspectral Image Classification Using Multiple Class-based Denoising Autoencoders, Mixed Pixel Training Augmentation, and Morphological Operations
Herein, we present a system for hyperspectral image segmentation that utilizes multiple class--based denoising autoencoders which are efficiently trained.
Conditional Random Field and Deep Feature Learning for Hyperspectral Image Segmentation
Image segmentation is considered to be one of the critical tasks in hyperspectral remote sensing image processing.
On distances, paths and connections for hyperspectral image segmentation
Then a finer segmentation is obtained by computing $\eta$-bounded regions and $\mu$-geodesic balls inside the $\lambda$-flat zones.
SegSALSA-STR: A convex formulation to supervised hyperspectral image segmentation using hidden fields and structure tensor regularization
We present a supervised hyperspectral image segmentation algorithm based on a convex formulation of a marginal maximum a posteriori segmentation with hidden fields and structure tensor regularization: Segmentation via the Constraint Split Augmented Lagrangian Shrinkage by Structure Tensor Regularization (SegSALSA-STR).
