Passive Terahertz Imaging Research Articles

室内人体隐匿物被动太赫兹成像研究进展

室内人体隐匿物被动太赫兹成像研究进展

The active-passive continuous-wave terahertz imaging system

Active and passive terahertz (THz) imaging have recently become essential instruments of various THz applications. In this paper the active- and passive-mode THz imaging systems are studied and the hybrid active-passive THz imaging system is suggested. The concept of image contrast was used to compare the active and passive THz imaging results. In order to achieve better image quality the hybrid system is considered to be effective. The main advantage of the proposed system is the combination of the self-emitted radiation of the object with the back scattered source radiation. The experimental results demonstrate that the active-passive modality of THz imaging system allows retrieving maximum information about the object. An approach to synthesise the active-passive THz images was proposed using the false-color representation.

Combined terahertz imaging system for enhanced imaging quality

An improved terahertz (THz) imaging system is proposed for enhancing image quality. Imaging scheme includes THz source and detection system operated in active mode as well as in passive one. In order to homogeneously illuminate the object plane the THz reshaper is proposed. The form and internal structure of the reshaper were studied by the numerical simulation. Using different test-objects we compare imaging quality in active and passive THz imaging modes. Imaging contrast and modulation transfer functions in active and passive imaging modes show drawbacks of them in high and low spatial frequencies, respectively. The experimental results confirm the benefit of combining both imaging modes into hybrid one. The proposed algorithm of making hybrid THz image is an effective approach of retrieving maximum information about the remote object.

A hybrid continuous-wave terahertz imaging system.

A hybrid (active-passive mode) terahertz (THz) imaging system and an algorithm for imaging synthesis are proposed to enhance the THz image quality. The concept of image contrast is used to compare active and passive THz imaging. Combining the measurement of the self-emitted radiation of the object with the back-scattered source radiation measurement, it becomes possible to use the THz image to retrieve maximum information about the object. The experimental results confirm the advantages of hybrid THz imaging systems, which can be generalized for a wide range of applications in the material sciences, chemical physics, bio-systems, etc.

パッシブテラヘルツイメージングによる道路環境認識技術

パッシブテラヘルツイメージングによる道路環境認識技術

Phase-Sensitive Passive Terahertz Imaging at 5-m Stand-Off Distance

A novel imaging modality for passive THz scanners is described. The method relies on the phase-sensitive detection of THz radiation which is emitted or reflected from the object under investigation. A blackbody which is implemented in the imaging system provides a reference source. By alternate viewing of the scene and the reference source, phase-sensitive detection with a lock-in amplifier is realized. This enables simultaneous intensity and phase detection. Experiments which demonstrate the capabilities of the detection scheme have been performed with a passive THz scanner for stand-off detection at 5-m distance. The system operates at 345 GHz. When choosing the effective temperature of the reference source as the average of the object and its surroundings, only the edges of the object under investigation were detected in the intensity domain. This is hardware-based edge detection, in contrast to software-based edge detection where edges in an image are determined by a software algorithm. An additional advantage is the phase detection which effectively acts as a threshold detector and can improve the signal-to-noise ratio. Because only edges are detected in this scheme, it seems feasible that the privacy problem is relaxed or the privacy problem might be overcome.

基于马尔可夫约束的被动式太赫兹图像复原

基于马尔可夫约束的被动式太赫兹图像复原

被动式太赫兹图像目标检测研究

被动式太赫兹图像目标检测研究

Detection and Segmentation of Concealed Objects in Terahertz Images

Terahertz imaging makes it possible to acquire images of objects concealed underneath clothing by measuring the radiometric temperatures of different objects on a human subject. The goal of this work is to automatically detect and segment concealed objects in broadband 0.1-1 THz images. Due to the inherent physical properties of passive terahertz imaging and associated hardware, images have poor contrast and low signal to noise ratio. Standard segmentation algorithms are unable to segment or detect concealed objects. Our approach relies on two stages. First, we remove the noise from the image using the anisotropic diffusion algorithm. We then detect the boundaries of the concealed objects. We use a mixture of Gaussian densities to model the distribution of the temperature inside the image. We then evolve curves along the isocontours of the image to identify the concealed objects. We have compared our approach with two state-of-the-art segmentation methods. Both methods fail to identify the concealed objects, while our method accurately detected the objects. In addition, our approach was more accurate than a state-of-the-art supervised image segmentation algorithm that required that the concealed objects be already identified. Our approach is completely unsupervised and could work in real-time on dedicated hardware.