Hundreds of narrow bands over a continuous spectral range make hyperspectral imagery rich in information about objects, while at the same time causing the neighboring bands to be highly correlated. Band selection is a technique that provides clear physical-meaning results for hyperspectral dimensional reduction, alleviating the difficulty for transferring and processing hyperspectral images caused by a property of hyperspectral images: large data volumes. In this study, a simple and efficient band ranking via extended coefficient of variation (BRECV) is proposed for unsupervised hyperspectral band selection. The naive idea of the BRECV algorithm is to select bands with relatively smaller means and lager standard deviations compared to their...
Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) pr...
Abstract—Hyperspectral imaging involves large amounts of in-formation. This paper presents a techniq...
International audienceThe most challenges problems in hyperspectral images processing are the huge a...
Hundreds of narrow bands over a continuous spectral range make hyperspectral imagery rich in informa...
The problem of band selection (BS) is of great importance to handle the curse of dimensionality for ...
AbstractWith the development of hyperspectral remote sensing technology, the spectral resolution of ...
International audienceIn order to alleviate the negative effect of curse of dimensionality, band sel...
Hyperspectral Band Selection (BS) aims to select a few informative and distinctive bands to represen...
Hyperspectral Band Selection (BS) aims to select a few informative and distinctive bands to represen...
We investigate band selection for hyperspectral image classification. Mutual information (MI) measur...
Feature selection especially band selection plays important roles in hyperspectral remote sensed ima...
Hyperspectral data offer refined spectral discrimination of ground targets, but come at a substantia...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
Despite the numerous band selection (BS) algorithms reported in the field, most if not all have exhi...
Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) pr...
Abstract—Hyperspectral imaging involves large amounts of in-formation. This paper presents a techniq...
International audienceThe most challenges problems in hyperspectral images processing are the huge a...
Hundreds of narrow bands over a continuous spectral range make hyperspectral imagery rich in informa...
The problem of band selection (BS) is of great importance to handle the curse of dimensionality for ...
AbstractWith the development of hyperspectral remote sensing technology, the spectral resolution of ...
International audienceIn order to alleviate the negative effect of curse of dimensionality, band sel...
Hyperspectral Band Selection (BS) aims to select a few informative and distinctive bands to represen...
Hyperspectral Band Selection (BS) aims to select a few informative and distinctive bands to represen...
We investigate band selection for hyperspectral image classification. Mutual information (MI) measur...
Feature selection especially band selection plays important roles in hyperspectral remote sensed ima...
Hyperspectral data offer refined spectral discrimination of ground targets, but come at a substantia...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
A novel unsupervised band selection method is proposed, where adaptive clustering of spectral compon...
Despite the numerous band selection (BS) algorithms reported in the field, most if not all have exhi...
Band selection has become a significant issue for the efficiency of the hyperspectral image (HSI) pr...
Abstract—Hyperspectral imaging involves large amounts of in-formation. This paper presents a techniq...
International audienceThe most challenges problems in hyperspectral images processing are the huge a...