Deep Learning Optimized Terahertz Single-Pixel Imaging

Abstract

In this article, we demonstrate an efficient terahertz single-pixel imaging system incorporating deep learning networks. Experimental results show that by combining a Hadamard single-pixel imaging system with the deep learning network, the sampling time per pattern can be reduced to 1/20 of the conventional system and the number of Hadamard patterns can be reduced to 10% of the pixels while maintaining high image quality with acceptable signal-to-noise ratio above 20 dB and structural similarity of more than 0.85. We thus expect this article to advance the development of a real-time terahertz single-pixel imaging system and promote its applications.