Abstract:
In this article, an unsupervised band elimination method for hyperspectral imagery has been proposed which iteratively eliminates one band from the pair of most correlate...Show MoreMetadata
Abstract:
In this article, an unsupervised band elimination method for hyperspectral imagery has been proposed which iteratively eliminates one band from the pair of most correlated neighboring bands depending on discriminating capability of the bands. Correlation between neighboring bands is calculated over partitioned band images. Capacitory discrimination is used to measure the discrimination capability of a band image. To demonstrate the effectiveness of the proposed method, results are compared with three state-of-the-art methods in terms of overall classification accuracy and Kappa coefficient. Results for the proposed methodology are found to be encouraging.
Published in: 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)
Date of Conference: 22-25 August 2013
Date Added to IEEE Xplore: 21 October 2013
ISBN Information: