Band Selection for Hyperspectral Image Classification Using Mutual Information

Spatial Mutual Information Based Hyperspectral Band Selection for Classification

The amount of information involved in hyperspectral imaging is large. Hyperspectral band selection is a popular method for reducing dimensionality. Several information based measures such as mutual information have been proposed to reduce information redundancy among spectral bands. Unfortunately, mutual information does not take into account the spatial dependency between adjacent pixels in im...

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...

Spatial Entropy Based Mutual Information in Hyperspectral Band Selection for Supervised Classification

Hyperspectral band image selection is a fundamental problem for hyperspectral remote sensing data processing. Accepting its importance, several information-based band selection methods have been proposed, which apply Shannon entropy to measure image information. However, the Shannon entropy is not accurate in measuring image information since it neglects the spatial distribution of pixels and i...

Firefly Based Band Selection for Hyperspectral Image Classification

Hyperspectral Data Selection from Mutual Information Between Image Bands

This work presents a band selection method for multi and hyperspectral images using correlation among bands based on mutual information measures. The relationship among bands are represented by means of the transinformation matrix. A process based on a Deterministic Annealing optimization is applied to the transinformation matrix in order to obtain a reduction of this matrix looking for the ima...