In this paper, we take a necessary first step towards the quantitative comparison of parallel techniques and strategies for analyzing hyperspectral data sets.

In this paper, we have examined different implementations of hyperspectral image processing algorithms, with the pur- pose of evaluating the possibility of ...

In this paper, we take a necessary first step towards the quantitative comparison of parallel techniques and strategies for analyzing hyperspectral data sets.

ABSTRACT. Many algorithms for spectral unmixing have been proposed in the last years applied on hyperspectral imaging. This process.

A Wavelet-based technique gives a reduced Hypercube rich in pixels spectrum features. ... A CNN is designed to classify different types of surfaces or materials.

Oct 25, 2018 · This paper introduces a novel DPA algorithm to accelerate an LRASR method for hyperspectral anomaly detection on cloud computing architectures.

Abstract—Automated extraction of spectral endmembers is a crucial task in hyperspectral data analysis. In most cases, the com-.

This work aims to propose a parallel implementation of a Gabor filter feature extraction method for hyperspectral images over a Graphics Processing Unit (GPU) ...

PDF | In this paper, we develop several parallel techniques for hyperspectral image processing that have been specifi-cally designed to be run on.

In this chapter, several techniques for classification of hyperspectral imagery using neural networks are presented and discussed. Experimental results are ...