Abstract-How Do Detected Objects Affect the Noise Distribution of Terahertz Security Images?

Zhaodi Wang, Menghan Hu,  Ercan Engin Kuruoglu, Wenhan Zhu,   Guangtao Zhai,

An alpha-stable distribution is used to fit the noise of Terahertz (THz) image. We found that there is a nonlinear effect caused by the testing person. This can be applied to design the filter and hardware for noise reduction.

https://ieeexplore.ieee.org/document/8418702/

The purpose of this paper is to analyze how detected objects affect the noise distribution of terahertz (THz) security images. Noise in THz image caused by hardware deteriorates the image quality seriously, limiting the application. In addition, there are a few papers on the noise analysis of THz screenings. Due to the special attributes of the THz image compared with the natural image, an alpha-stable distribution is used to fit the noise of THz image instead of the commonly-used Gaussian distribution. The database used in this paper is composed of 181 THz image cubes with a test object as well as two empty image cubes. After analyzing the four parameters of alpha-stable distribution, we can observe that the noise patterns of THz images are indeed different from those of natural image obtained by RGB camera. The possible reasons are given based on the principles of the THz imaging device. The analysis of the distribution of four parameters of alpha-stable model demonstrates that there exists a nonlinear effect due to the change of reflected wave’s pattern caused by the body structure. This paper provides an efficient and flexible model for THz images and a useful guidance for the design of THz image denoising algorithms and the development of imaging hardware.

Abstract-How do detected objects affect the noise distribution of Terahertz security images?

Zhaodi Wang, Menghan Hu,   Ercan Engin Kuruoglu,  Wenhan Zhu,   Guangtao Zhai,

https://ieeexplore.ieee.org/document/8418702/

The purpose of this study is to analyze how detected objects affect the noise distribution of THz security images. Noise in THz image caused by hardware deteriorates the image quality seriously, limiting the application. In addition, there are few papers on the noise analysis of THz screenings. Due to the special attributes of the THz image compared to the natural image, an alpha-stable distribution is used to fit the noise of THz image instead of the commonly-used Gaussian distribution. The database used in this study is composed of 181 THz image cubes with a test object as well as 2 empty image cubes. After analyzing the four parameters of alpha-stable distribution, we can observe that the noise patterns of THz images are indeed different from those of natural image obtained by RGB camera. The possible reasons are given based on the principles of the THz imaging device. The analysis of the distribution of four parameters of alpha-stable model demonstrates that there exists a nonlinear effect due to the change of reflected wave’s pattern caused by the body structure. This study provides an efficient and flexible model for THz images and a useful guidance for the design of THz image denoising algorithms and the development of imaging hardware.

Abstract-Terahertz Security Image Quality Assessment by No-reference Model Observers

Menghan Hu, Xiongkuo Min, Guangtao Zhai, Wenhan Zhu, Zhaodi Wang, Xiaokang Yang, Guang Tian

(Submitted on 12 Jul 2017)

https://au.arxiv.org/abs/1707.03574

To provide the possibility of developing objective image quality assessment (IQA) algorithms for THz security images, we constructed the THz security image database (THSID) including a total of 181 THz security images with the resolution of 127*380. The main distortion types in THz security images were first analyzed for the design of subjective evaluation criteria to acquire the mean opinion scores. Subsequently, the existing no-reference IQA algorithms, which were 5 opinion-aware approaches viz., NFERM, GMLF, DIIVINE, BRISQUE and BLIINDS2, and 8 opinion-unaware approaches viz., QAC, SISBLIM, NIQE, FISBLIM, CPBD, S3 and Fish_bb, were executed for the evaluation of the THz security image quality. The statistical results demonstrated the superiority of Fish_bb over the other testing IQA approaches for assessing the THz image quality with PLCC (SROCC) values of 0.8925 (-0.8706), and with RMSE value of 0.3993. The linear regression analysis and Bland-Altman plot further verified that the Fish__bb could substitute for the subjective IQA. Nonetheless, for the classification of THz security images, we tended to use S3 as a criterion for ranking THz security image grades because of the relatively low false positive rate in classifying bad THz image quality into acceptable category (24.69%). Interestingly, due to the specific property of THz image, the average pixel intensity gave the best performance than the above complicated IQA algorithms, with the PLCC, SROCC and RMSE of 0.9001, -0.8800 and 0.3857, respectively. This study will help the users such as researchers or security staffs to obtain the THz security images of good quality. Currently, our research group is attempting to make this research more comprehensive.