Mr. Jingyao Wu Profile

Jingyao Wu

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Proceedings Article | 15 January 2021 Paper

Modeling and simulation analysis of a non-line-of-sight infrared laser imaging system

Jingjing Tan, Xiuqin Su, Kaidi Wang, Jingyao Wu

Proceedings Volume 11761, 117610M (2021) https://doi.org/10.1117/12.2585336

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Non-line-of-sight (NLOS) imaging technology is to ‘see’ the target out of sight, such as an object around a corner or hidden by some shelters. However, due to constraints of device definition and computing load, NLOS system is usually expensive and requires hidden objects with special material and simple shape. Besides, imaging space of system is limited. We perform a series of simulation with 1550nm infrared laser to expand the application field and improve the performance of NLOS system. Based on math and physical properties, main experimental components are modeled and data acquisition process is completed first. Then, the ellipsoid inversion algorithm is used to reconstruct the hidden space and imaging results are obtained. Finally, multiple series of system parameters are set and their influence on imaging results is analyzed. Results demonstrate that echo signal intensity after multiple reflections provides adequate information to reconstruct the geometry of a hidden object. However, the number of laser scanning position, resolution of detector, voxel division and location of the scanning area will all have a critical influence on NLOS imaging results.

Proceedings Article | 24 October 2017 Paper

Simulation of NLOS (non-line-of-sight) 3D imaging system

Jingjing Tan, Xiuqin Su, Jingyao Wu, Zhaoqi Wei

Proceedings Volume 10457, 104571A (2017) https://doi.org/10.1117/12.2284097

KEYWORDS: Imaging systems, Stereoscopy

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This passage studies on theory and scene simulation of NLOS imaging. Based on math and physical properties, a simulation platform is built for a NLOS imaging system, including a femtosecond laser, a scanning galvo system, a lambertian surface, several hidden scenes, an ultrafast photodetector to transfer the intensity of laser echo signal to voltage value and a TCSPC module to produce intensity-time histograms. By the simulation platform on MATLAB, precise imaging of the scenes is accomplished. Results show that multi-path analysis using echo signal intensity versus time provides enough proof to reconstruct 3D geometry of a hidden scene.

Proceedings Article | 24 October 2017 Paper

Laser spot center location algorithm based on sub-pixel interpolation

Tong Liu, Yan Tian, Jingyao Wu

Proceedings Volume 10462, 1046235 (2017) https://doi.org/10.1117/12.2285027

KEYWORDS: Laser processing, Image processing

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Precise location of laser spot in laser precision measurement is always an important research direction. Laser has the characteristics of good direction and small divergence, so it is widely used in aerospace, weapon systems and optical measuring and testing instruments. The accuracy of the laser spot center location can directly determine the precision of measurement. Aiming at positioning the center of laser spot, in the foundation of researching the limitation of the practical application of the common laser spot center location algorithm, this paper proposes a method of laser spot center localization based on sub-pixel interpolation, which can effectively improve the signal noise ratio (SNR) of laser spot image, reduce the influence of the background noise and thermal noise. The algorithm firstly uses the threshold value decision to exclude the interference of the light of the image, and then use the improved sub-pixel interpolation algorithm for image edge detection to obtain the edge image, and finally using the circle fitting method to obtain the positioning center. Through the experiment of processing of laser spot image, the results show that improved algorithm proposed in this paper has higher positioning accuracy than the traditional centroid, and satisfies the need of laser precision measurement in reliability, positioning accuracy and noise resistance and other aspects, at the same time, the computational complexity of this algorithm is low, can greatly save the system resources, and it can be used for the processing of the video images in the hardware and software.

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