Multiple Classifier Ensembles with Band Clustering for Hyperspectral Image Classification

Multiple Classifier Ensembles with Band Clustering for Hyperspectral Image Classification

Due to the high dimensionality of a hyperspectral image, classification accuracy of a single classifier may be limited when the size of the training set is small. A divide-and-conquer approach has been proposed, where a classifier is applied to each group of bands and the final output will be the fused result of multiple classifiers. Since the dimensionality in each band group is much lower, cl...

Band Subset Selection for Hyperspectral Image Classification

This paper develops a new approach to band subset selection (BSS) for hyperspectral image classification (HSIC) which selects multiple bands simultaneously as a band subset, referred to as simultaneous multiple band selection (SMMBS), rather than one band at a time sequentially, referred to as sequential multiple band selection (SQMBS), as most traditional band selection methods do. In doing so...

Hyperspectral Image Classification Using Graph Clustering Methods

Hyperspectral imagery is a challenging modality due to the dimension of the pixels which can range from hundreds to over a thousand frequencies depending on the sensor. Most methods in the literature reduce the dimension of the data using a method such as principal component analysis, however this procedure can lose information. More recently methods have been developed to address classificatio...

Firefly Based Band Selection for Hyperspectral Image Classification

A joint band prioritization and band-decorrelation approach to band selection for hyperspectral image classification

Band selection for remotely sensed image data is an effective means to mitigate the curse of dimensionality. Many criteria have been suggested in the past for optimal band selection. In this paper, a joint band-prioritization and band-decorrelation approach to band selection is considered for hyperspectral image classification. The proposed band prioritization is a method based on the eigen (sp...