Adaptive compressed sensing for the fast terahertz reflection tomography

Kijun Kim; Dong Gyu Lee; Woo Gyu Ham; Jaseong Ku; Sang Hun Lee; Chang Beom Ahn; Joo Hiuk Son; Hochong Park

doi:10.1109/TTHZ.2013.2267417

Adaptive compressed sensing for the fast terahertz reflection tomography

Kijun Kim, Dong Gyu Lee, Woo Gyu Ham, Jaseong Ku, Sang Hun Lee, Chang Beom Ahn, Joo Hiuk Son, Hochong Park

Department of Physics

Research output: Contribution to journal › Article › peer-review

8 Scopus citations

Abstract

In this paper, an adaptive compressed sensing is proposed in order to enhance the performance of fast tetrahertz reflection tomography. The proposed method first acquires data at random measurement points in the spatial domain, and estimates the regions in each tomographic image where much degradation is expected. Then, it allocates additional measurement points to those regions, so that more data are acquired adaptively at the regions prone to degradation, thereby improving the quality of the reconstructed tomographic images. The proposed method was applied to the T-ray reflection tomography system, and the image quality enhancement by the proposed method, compared to the conventional method, was verified for the same number of measurement points.

Original language	English
Article number	6549175
Pages (from-to)	395-401
Number of pages	7
Journal	IEEE Transactions on Terahertz Science and Technology
Volume	3
Issue number	4
DOIs	https://doi.org/10.1109/TTHZ.2013.2267417
State	Published - Jul 2013

Keywords

Compressed sensing (CS)
THz tomography
Tetrahertz (THz) imaging

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10.1109/TTHZ.2013.2267417

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abstract = "In this paper, an adaptive compressed sensing is proposed in order to enhance the performance of fast tetrahertz reflection tomography. The proposed method first acquires data at random measurement points in the spatial domain, and estimates the regions in each tomographic image where much degradation is expected. Then, it allocates additional measurement points to those regions, so that more data are acquired adaptively at the regions prone to degradation, thereby improving the quality of the reconstructed tomographic images. The proposed method was applied to the T-ray reflection tomography system, and the image quality enhancement by the proposed method, compared to the conventional method, was verified for the same number of measurement points.",

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AU - Kim, Kijun

AU - Lee, Dong Gyu

AU - Ham, Woo Gyu

AU - Ku, Jaseong

AU - Lee, Sang Hun

AU - Ahn, Chang Beom

AU - Son, Joo Hiuk

AU - Park, Hochong

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AB - In this paper, an adaptive compressed sensing is proposed in order to enhance the performance of fast tetrahertz reflection tomography. The proposed method first acquires data at random measurement points in the spatial domain, and estimates the regions in each tomographic image where much degradation is expected. Then, it allocates additional measurement points to those regions, so that more data are acquired adaptively at the regions prone to degradation, thereby improving the quality of the reconstructed tomographic images. The proposed method was applied to the T-ray reflection tomography system, and the image quality enhancement by the proposed method, compared to the conventional method, was verified for the same number of measurement points.

KW - Compressed sensing (CS)

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Adaptive compressed sensing for the fast terahertz reflection tomography

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Keywords

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