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Proceedings Paper

PCA-based visualization of terahertz time-domain spectroscopy image
Author(s): Jihong Pei; Yong Hu; Weixin Xie
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Paper Abstract

A novel visualization method of terahertz time-domain spectroscopy (THz-TDS) image is presented, which is based on principal component analysis (PCA) technique. The proposed method include three processing steps: firstly, the THz- TDS image is preprocessed using a spatial vector filtering technique to denoise. Secondly, the THz-TDS image is transformed from spatio-temporal domain to spatio-spectral domain, and the transformed image can be viewed as a multispectral image whose spectral dimensionality D is equal to the sampled number of THz-TDS pulse at each pixel. Thirdly, each of spectrum vector at a pixel is viewed as a point in D dimensional space, the covariance matrix of pixels can be computed, and then three eigenvectors corresponding to the first 3 largest eigenvalues are found by PCA technique. the THz-TDS image is projected along these three eigenvectors. By normalizing these 3 principal component images and mapping them into the RGB space, we can get a synthetic color image as a visualization result of the THz- TDS image. Due to vector-based dimensionality reduction, the proposed method can provide more visual information of the THz-TDS image than scalar-based visualization techniques. Finally, experimental results are provided to demonstrate the performance of the proposed method.

Paper Details

Date Published: 15 November 2007
PDF: 7 pages
Proc. SPIE 6787, MIPPR 2007: Multispectral Image Processing, 67871M (15 November 2007); doi: 10.1117/12.749995
Show Author Affiliations
Jihong Pei, Shenzhen Univ. (China)
Yong Hu, Shenzhen Univ. (China)
Weixin Xie, Shenzhen Univ. (China)

Published in SPIE Proceedings Vol. 6787:
MIPPR 2007: Multispectral Image Processing
Henri Maître; Hong Sun; Jianguo Liu; Enmin Song, Editor(s)

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