Berry, E., Boyle, R.D., Fitzgerald, A.J. and Handley, J.W. (2005) Time frequency analysis in terahertz pulsed imaging. In: Bhanu, B. and Pavlidis, I., (eds.) Computer Vision: Beyond the Visible Spectrum. Advances in Pattern Recognition . Springer Verlag , London, UK , pp. 290-329. ISBN 1 -85233-604-8Full text available as:
Available under licence : See the attached licence file.
Recent advances in laser and electro-optical technologies have made the previously under-utilized terahertz frequency band of the electromagnetic spectrum accessible for practical imaging. Applications are emerging, notably in the biomedical domain. In this chapter the technique of terahertz pulsed imaging is introduced in some detail. The need for special computer vision methods, which arises from the use of pulses of radiation and the acquisition of a time series at each pixel, is described. The nature of the data is a challenge since we are interested not only in the frequency composition of the pulses, but also how these differ for different parts of the pulse. Conventional and short-time Fourier transforms and wavelets were used in preliminary experiments on the analysis of terahertz pulsed imaging data. Measurements of refractive index and absorption coefficient were compared, wavelet compression assessed and image classification by multidimensional clustering techniques demonstrated. It is shown that the timefrequency methods perform as well as conventional analysis for determining material properties. Wavelet compression gave results that were robust through compressions that used only 20% of the wavelet coefficients. It is concluded that the time-frequency methods hold great promise for optimizing the extraction of the spectroscopic information contained in each terahertz pulse, for the analysis of more complex signals comprising multiple pulses or from recently introduced acquisition techniques.
|Item Type:||Book Section|
|Copyright, Publisher and Additional Information:||Copyright © 2005 Springer. This is an author produced version of a chapter published in Computer Vision: Beyond the Visible Spectrum.|
|Institution:||The University of Leeds|
|Academic Units:||The University of Leeds > Faculty of Engineering (Leeds) > School of Computing (Leeds)
The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Genetics, Health and Therapeutics (LIGHT) > Academic Unit of Medical Physics (Leeds)
The University of Leeds > University of Leeds Research Centres and Institutes > Centre for Medical Imaging Research (Leeds)
|Depositing User:||Elizabeth Berry|
|Date Deposited:||13 Mar 2006|
|Last Modified:||05 Jun 2014 22:16|