Dr. Junchen Song Profile

Dr. Junchen Song

at Xi'an Research Institute of High Technology

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Publications (2)

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Proceedings Article | 1 June 2021 Paper

Novel polarization-maintaining fiber sensor based on magneto-optical modulation for transverse pressure measurement

Zhiyong Yang, Junchen Song, Wei Cai, Gaoxiang Lu

Proceedings Volume 11848, 118480K (2021) https://doi.org/10.1117/12.2600354

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A novel polarization-maintaining fiber sensor based on magneto-optical modulation for transverse stress measurement is proposed. The composition of the sensor system is introduced in detail. Polarized light is used as the stress information carrier, and magneto-optical modulation is used to improve the anti-interference and sensitivity of the system. According to the light phase change caused by the elastic optical effect, the theoretical relationship between the azimuth angle and the transverse pressure is derived in detail through the change of the Jones matrix. The technology extends the new measurement method of polarization-maintaining fiber in the sensor field and has certain reference value in the field of micro-pressure measurement.

Proceedings Article | 1 June 2021 Paper

Algorithm of infrared-polarization image fusion based on fireworks algorithm

Zhiyong Yang, Gaoxiang Lu, Wei Cai, Danqiu Qiao, Junchen Song

Proceedings Volume 11848, 118481H (2021) https://doi.org/10.1117/12.2600157

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Because of the shortcomings of traditional infrared-polarization image fusion algorithm, such as low intelligence and single optimization index, this paper proposes an intelligent infrared-polarization image fusion optimization algorithm based on fireworks algorithm. Based on the strong complementarity between infrared-intensity image and degree of linearpolarization (DOLP) image and the explosive optimization of fireworks algorithm, the problem model of weighted fusion algorithm is established, and the fitness function based on root mean square error (RMSE) is constructed to calculate the optimal weight of source image. In the fusion experiment of long-wave infrared-intensity image and DOLP image, this method is compared with the common fusion algorithms. The results show that this method can effectively fuse the infrared-intensity and degree of polarization information, and the evaluation indexes of standard deviation, spatial frequency, mutual information, structural similarity, peak signal-to-noise ratio and information entropy of the fusion image are better than the comparison algorithm. In the future, cooperated with the long-wave infrared-polarization imaging system, this method can be applied to improve the infrared detection ability in complex environment.

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