We propose and analyze a new model for hyperspectral images (HSIs) based on the
assumption that the whole signal is composed of a linear combination of few sources, each …

Hyperspectral imaging (HSI) is an emerging technique, which provides the continuous
acquisition of electro-magnetic waves, usually covering the visible as well as the infrared …

Hyperspectral imaging (HSI) is a useful tool for the classification of vast areas. High
accuracy is achieved by means of spectral information for each pixel, which inherently leads …

This paper describes a novel framework for compressive sampling (CS) of multichannel
signals that are highly dependent across the channels. In this work, we assume few number …

Imaging mass spectrometry (IMS) is a technique of analytical chemistry for spatially
resolved, label-free and multipurpose analysis of biological samples that is able to detect the …

We adopt a data structure in the form of cover trees and iteratively apply approximate
nearest neighbour (ANN) searches for fast compressed sensing reconstruction of signals …

Compressive sensing (CS) is a new emerging approach in recent years, and is applied in
acquisition of signals having a sparse or compressible representation in some basis. The …

Compressed hyperspectral image reconstruction plays an important role in hyperspectral
image processing, which aims to reduce the cost of transmission and recover the …

Denne studien presenterer og diskuterer ulike komponenter i en pipeline, inkludert
deteksjon og fjerning av skyer, gjenoppretting av manglende områder, og rekonstruksjon av" …

We introduce a new constrained minimization problem that performs template and pattern
detection on a multispectral image in a compressive sensing context. We use an original …