Hyperspectral Band Selection for Multispectral Image Classification with Convolutional Networks

by   Giorgio Morales, et al.

In recent years, Hyperspectral Imaging (HSI) has become a powerful source for reliable data in applications such as remote sensing, agriculture, and biomedicine. However, hyperspectral images are highly data-dense and often benefit from methods to reduce the number of spectral bands while retaining the most useful information for a specific application. We propose a novel band selection method to select a reduced set of wavelengths, obtained from an HSI system in the context of image classification. Our approach consists of two main steps: the first utilizes a filter-based approach to find relevant spectral bands based on a collinearity analysis between a band and its neighbors. This analysis helps to remove redundant bands and dramatically reduces the search space. The second step applies a wrapper-based approach to select bands from the reduced set based on their information entropy values, and trains a compact Convolutional Neural Network (CNN) to evaluate the performance of the current selection. We present classification results obtained from our method and compare them to other feature selection methods on two hyperspectral image datasets. Additionally, we use the original hyperspectral data cube to simulate the process of using actual filters in a multispectral imager. We show that our method produces more suitable results for a multispectral sensor design.


Unsupervised Band Selection of Hyperspectral Images via Multi-dictionary Sparse Representation

Hyperspectral images have far more spectral bands than ordinary multispe...

Deep Reinforcement Learning for Band Selection in Hyperspectral Image Classification

Band selection refers to the process of choosing the most relevant bands...

Ensemble Hyperspectral Band Selection for Detecting Nitrogen Status in Grape Leaves

The large data size and dimensionality of hyperspectral data demands com...

An automatic bad band preremoval algorithm for hyperspectral imagery

For most hyperspectral remote sensing applications, removing bad bands, ...

Band selection with Higher Order Multivariate Cumulants for small target detection in hyperspectral images

In the small target detection problem a pattern to be located is on the ...

SRL-SOA: Self-Representation Learning with Sparse 1D-Operational Autoencoder for Hyperspectral Image Band Selection

The band selection in the hyperspectral image (HSI) data processing is a...

Please sign up or login with your details

Forgot password? Click here to reset