Deep learning is a rather new approach to machine learning that has achieved remarkable
results in a large number of different image processing applications. Lately, application of …

Hyperspectral images (HSIs) contain subtle spectral details and rich spatial contextures of
land cover that benefit from developments in spectral imaging and space technology. The …

Hyperspectral image (HSI) analysis often requires selecting the most informative bands
instead of processing the whole data without losing the key information. Existing band …

Hyperspectral Image analysis has gained much attention due to the presence of rich
spectral information. Hyperspectral Image (HSI) classification is being utilized in a wide …

This work addresses the problem of hyperspectral data compression and the evaluation of
the reconstruction quality for different compression rates. Data compression is intended to …

This work addresses the challenge of the portability of Autoencoder models for the lossy
compression of different spatially independent and unknown hyperspectral satellite data. We …

Recently, several feature extraction techniques have been exploited to resolve the
hyperspectral dimension reduction issue. Feature extraction methods can be widely …

This work addresses the problem of hyperspectral data compression and compares the
reconstruction accuracy for different compression rates. Through data compression, the …