Add to ORKGThis work presents the application of a novel technique on dimensionality reduction to deal with multispectral images. A distance based on mutual information is used to construct a hierarchical clustering structure. Experimental results show that the method provides a very suitable subset of multispectral bands for pixel classification purposes. 1
Hyperspectral image is a substitution of more than a hundred im-ages, called bands, of the same regi...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
The hyperspectral data contains hundreds of narrows bands representing the same scene on earth, with...
This work presents the application of a novel technique on dimensionality reduction to deal with mul...
Abstract—Hyperspectral imaging involves large amounts of in-formation. This paper presents a techniq...
The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection i...
Copyright © 2015 Anthony Amankwah.This is an open access article distributed under theCreativeCommon...
The hyperspectral data contains hundreds of narrows bands representing the same scene on earth, with...
Hyperspectral data offer refined spectral discrimination of ground targets, but come at a substantia...
Abstract�Hyperspectral systems produce a massive amount of data. Dimensionality reduction pays an im...
Abstract—In this paper, a band selection technique for hyperspectral image data is proposed. Supervi...
Hyperspectral images (HIS) classification is a high technical remote sensing tool. The goal is to re...
International audienceWe address the problem of unsupervised band reduction in hyperspectral remote ...
International audienceWe address the problem of unsupervised band reduction in hyperspectral remote ...
International audienceWe address the problem of unsupervised band reduction in hyperspectral remote ...
Hyperspectral image is a substitution of more than a hundred im-ages, called bands, of the same regi...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
The hyperspectral data contains hundreds of narrows bands representing the same scene on earth, with...
This work presents the application of a novel technique on dimensionality reduction to deal with mul...
Abstract—Hyperspectral imaging involves large amounts of in-formation. This paper presents a techniq...
The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection i...
Copyright © 2015 Anthony Amankwah.This is an open access article distributed under theCreativeCommon...
The hyperspectral data contains hundreds of narrows bands representing the same scene on earth, with...
Hyperspectral data offer refined spectral discrimination of ground targets, but come at a substantia...
Abstract�Hyperspectral systems produce a massive amount of data. Dimensionality reduction pays an im...
Abstract—In this paper, a band selection technique for hyperspectral image data is proposed. Supervi...
Hyperspectral images (HIS) classification is a high technical remote sensing tool. The goal is to re...
International audienceWe address the problem of unsupervised band reduction in hyperspectral remote ...
International audienceWe address the problem of unsupervised band reduction in hyperspectral remote ...
International audienceWe address the problem of unsupervised band reduction in hyperspectral remote ...
Hyperspectral image is a substitution of more than a hundred im-ages, called bands, of the same regi...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
The hyperspectral data contains hundreds of narrows bands representing the same scene on earth, with...