Terahertz Image Super-Resolution Reconstruction of Passive Safety Inspection Based on Generative Adversarial Network

Wan, Yibin; Zhang, Rongyue; Hong, Xia; Wang, Hao; Pan, Yihao; Zhou, Yue

doi:10.1109/ithings/greencom/cpscom/smartdata.2019.00027

Cited by 5 publications

(1 citation statement)

References 11 publications

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“…Terahertz (THz) waves lie between 0.1 to 10 THz with high penetrability and nonionizing characteristics. They have been widely used in non-destructive testing [1], biomedical diagnosis [2][3][4], industrial [5], and safety testing [6], etc. The long-wavelength of the THz wave leads that the imaging resolution is deteriorated with diffraction.…”

Section: Introductionmentioning

confidence: 99%

Terahertz Image Super-Resolution Reconstruction Based on Complex Deconvolution Algorithm with Different Criteria

Wang

Feng

Wang

2021

2021 the 6th International Conference on Information Systems Engineering

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Super-Resolution (SR) is one of the most fundamental issues in THz imaging processing. Deconvolution is widely used in THz imaging SR problems. Heavy-tailed distribution has good performance in deconvolution for its capability to preserve edges. By making use of the wave nature of THz waves, complex deconvolution is employed for solving THz images. A complex deconvolution algorithm based on criteria is proposed in this paper. And three criteria are discussed to get the most optimal result. Compared with the traditional methods, which are set the index as a fixed value, our method is more flexible for obtaining clear edges. The measured PSF is used to analyze the THz image by a complex image blurred model. Experiments illustrate the efficiency and accuracy of the proposed method. All three criteria can solve the LR problem well. Relative to Peak Signal to Noise Ratio (PSNR) and information entropy, the SR result of Structural Similarity Index Measure (SSIM) is better visual. Thus, we prefer SSIM as the criterion in our work.

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Section: Introductionmentioning

confidence: 99%

Terahertz Image Super-Resolution Reconstruction Based on Complex Deconvolution Algorithm with Different Criteria

Wang

Feng

Wang

2021

2021 the 6th International Conference on Information Systems Engineering

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Machine Learning and Application in Terahertz Technology: A Review on Achievements and Future Challenges

Jiang

et al. 2022

IEEE Access

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Terahertz (THz) radiation (0.1~10 THz) shows great potential in agricultural products detection, biomedical, and security inspection in recent years. Machine learning methods are widely used to support the user demand of higher efficiency and high prediction accuracy. The technological and key challenges of machine learning methods are for THz spectroscopy and image data preprocessing, reconstruction algorithms, and qualitative and quantitative analysis. In this paper, an exhaustive review of recent related works of THz detection and imaging techniques and machine learning methods are presented. The application of machine learning methods combined with THz technology in quality inspection of agricultural products, biomedical, security inspection, and materials science are highlighted. Challenges of machine learning methods for these applications are addressed. The development trend and future perspectives of THz technology are also discussed.INDEX TERMS terahertz spectrum, terahertz imaging, machine learning, agricultural products, detection application.

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THz Super-Resolution Imaging Based on Complex Laplacian Prior Deconvolution Algorithm

Wang

Feng

Wang

2021

2021 33rd Chinese Control and Decision Conference (CCDC)

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Terahertz Image Super-Resolution Reconstruction of Passive Safety Inspection Based on Generative Adversarial Network

Cited by 5 publications

References 11 publications

Terahertz Image Super-Resolution Reconstruction Based on Complex Deconvolution Algorithm with Different Criteria

Terahertz Image Super-Resolution Reconstruction Based on Complex Deconvolution Algorithm with Different Criteria

Machine Learning and Application in Terahertz Technology: A Review on Achievements and Future Challenges

THz Super-Resolution Imaging Based on Complex Laplacian Prior Deconvolution Algorithm

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