Research on BP neural network for terahertz image segmentation

Yu-Tong Wang; Qi Li; Yue Wang

doi:10.1117/12.2547541

20 December 2019 Research on BP neural network for terahertz image segmentation

Yu-Tong Wang, Qi Li, Yue Wang

Proceedings Volume 11209, Eleventh International Conference on Information Optics and Photonics (CIOP 2019); 112091N (2019) https://doi.org/10.1117/12.2547541
Event: Eleventh International Conference on Information Optics and Photonics (CIOP 2019), 2019, Xi'an, China

Abstract

Terahertz digital holographic reconstructed images are vulnerable to noise pollution. This paper uses neural network to segment terahertz image, because this method is insensitive to noise. Firstly, the training sample image is decomposed into several sub-images, and the backward propagation(BP) neural network is trained by them. At the same time, the optimal number of hidden layer neurons is selected. Then the trained neural network is applied to the segmentation of terahertz image. Different segmentation results are obtained by changing the variance of noise in the training sample image. The best segmentation results and training samples are determined by using the mean structural similarity(MSSIM). Finally, compared with the classical image segmentation algorithm, the results show that the segmentation effect of the neural network is better.

Citation Download Citation

Yu-Tong Wang, Qi Li, and Yue Wang "Research on BP neural network for terahertz image segmentation", Proc. SPIE 11209, Eleventh International Conference on Information Optics and Photonics (CIOP 2019), 112091N (20 December 2019); https://doi.org/10.1117/12.2547541

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