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Non-Parametric Spatial Spectral Band Selection methods
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publication may be reproduced without the written permission of the
copyright ownerThis project is about the development of band selection (BS) techniques for better
target detection and classification in remote sensing and hyperspectral imaging
(HSI). Conventionally, this is achieved just by using the spectral features for
guiding the band compression. However, this project develops a BS method
which uses both spatial and spectral features to allow a handful of crucial spectral
bands to be selected for enhancing the target detection and classification
performances.
This thesis firstly outlines the fundamental concepts and background of remote
sensing and HSI, followed by the theories of different atmospheric correction
algorithms — in order to assess the reflectance conversion for band selection —
and BS techniques, with a detailed explanation of the Hughes principle, which
postulates the fundamental drawback for having high-dimensional data in HSI.
Subsequently, the thesis highlights the performances of some advanced BS
techniques and to point out their deficiencies. Most of the existing BS work in the field have exhibited maximal classification
accuracy when more spectral bands have been utilized for classification; this
apparently disagrees with the theoretical model of the Hughes phenomenon. The
thesis then presents a spatial spectral mutual information (SSMI) BS scheme
which utilizes a spatial feature extraction technique as a pre-processing step,
followed by the clustering of the mutual information (MI) of spectral bands for
enhancing the BS efficiency. Through this BS scheme, a sharp ’bell’-shaped
accuracy-dimensionality characteristic has been observed, peaking at about 20
bands.
The performance of the proposed SSMI BS scheme has been validated through
6 HSI datasets, and its classification accuracy is shown to be ~10% better than 7
state-of-the-art BS algorithms. These results confirm that the high efficiency of
the BS scheme is essentially important to observe, and to validate, the Hughes
phenomenon at band selection through experiments for the first time.PH