Terahertz Imaging of Binary Reflectance with Variational Bayesian Inference

Pu Wang; Toshiaki Koike-Akino; Philip V. Orlik; Haoyu Fu; Yuejie Chi

ICASSP 2018accepted0 citations

Terahertz Imaging of Binary Reflectance with Variational Bayesian Inference

Pu Wang, Toshiaki Koike-Akino, Philip V. Orlik, Haoyu Fu, Yuejie Chi

Abstract

In this paper, we propose a Bayesian inference approach to extract the binary reflectance pattern of samples from compressed measurements in the terahertz (THz) frequency band. Compared with existing compressed THz imaging methods relying on the sparsity of the reflectance pattern, the proposed Bayesian approach exploits the non-negative binary nature of the reflectance without any assumption on its spatial pattern information and enables a pixel-wise iterative inference approach for fast signal recovery. Numerical evaluation confirms the effectiveness of the proposed approach.

BibTeX

@inproceedings{icassp2018_terahertzimaging,
  title = {Terahertz Imaging of Binary Reflectance with Variational Bayesian Inference},
  author = {Pu Wang and Toshiaki Koike-Akino and Philip V. Orlik and Haoyu Fu and Yuejie Chi},
  booktitle = {ICASSP 2018},
  year = {2018}
}