A survey of band selection techniques for hyperspectral image classification

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...

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...

A Band Selection Method for Hyperspectral Image Classification based on Improved Particle Swarm Optimization

With the development of spectral imaging technology, it makes hyperspectral imagery widely used. According to the features of multiple bands and the strong mutual correlation among these bands, this paper presents a band selection method for hyperspectral imagery classification based on improved PSO (Particle Swarm Optimization). First of all, we use information divergence to describe the corre...

Band Selection with CFI and Supervised Classification for Hyperspectral Images

In this paper, we propose a new feature selection method for hyperspectral images. Firstly, the bands are selected by combining the information entropy, classification separability and correlation coefficients with the Choquet fuzzy integral. After that, maximum likelihood classification method is used for the classification. Experiments on the AVIRIS dataset show that the proposed method remov...