Computer Vision Beyond the Visible Spectrum

Part of the series Advances in Pattern Recognition pp 271-311

Time-Frequency Analysis in Terahertz-Pulsed Imaging

  • Elizabeth BerryAffiliated withAcademic Unit of Medical Physics, University of Leeds
  • , Roger D BoyleAffiliated withSchool of Computing, Centre of Medical Imaging Research
  • , Anthony J FitzgeraldAffiliated withTeraview Ltd.
  • , James W HandleyAffiliated withSchool of Computing, Centre of Medical Imaging Research

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Recent advances in laser and electro-optical technologies have made the previously underutilized 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 multi dimensional clustering techniques demonstrated. It is shown that the time-frequency 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.