Unsupervised Segmentation of Hyper-spectral Images via Diffusion Bases

Alon Schclar, Amir Averbuch

2017

Abstract

In the field of hyper-spectral sensing, sensors capture images at hundreds and even thousands of wavelengths. These hyper-spectral images, which are composed of hyper-pixels, offer extensive intensity information which can be utilized to obtain segmentation results which are superior to those that are obtained using RGB images. However, straightforward application of segmentation is impractical due to the large number of wavelength images, noisy wavelengths and inter-wavelength correlations. Accordingly, in order to efficiently segment the image, each pixel needs to be represented by a small number of features which capture the structure of the image. In this paper we propose the diffusion bases dimensionality reduction algorithm to derive the features which are needed for the segmentation. We also propose a simple algorithm for the segmentation of the dimensionality reduced image. We demonstrate the proposed framework when applied to hyper-spectral microscopic images and hyper-spectral images obtained from an airborne hyper-spectral camera.

Download


Paper Citation


in Harvard Style

Schclar A. and Averbuch A. (2017). Unsupervised Segmentation of Hyper-spectral Images via Diffusion Bases.In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI, ISBN 978-989-758-274-5, pages 305-312. DOI: 10.5220/0006503503050312


in Bibtex Style

@conference{ijcci17,
author={Alon Schclar and Amir Averbuch},
title={Unsupervised Segmentation of Hyper-spectral Images via Diffusion Bases},
booktitle={Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,},
year={2017},
pages={305-312},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006503503050312},
isbn={978-989-758-274-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: IJCCI,
TI - Unsupervised Segmentation of Hyper-spectral Images via Diffusion Bases
SN - 978-989-758-274-5
AU - Schclar A.
AU - Averbuch A.
PY - 2017
SP - 305
EP - 312
DO - 10.5220/0006503503050312