Fourier Single-Pixel Imaging Based on Online Modulation Pattern Binarization

• DOI: 10.3390/photonics10090963
• Publication Date: 2023-08-23T12:20:30Z
• Authors: Xinding Jiang; Ziyi Tong; Zhongyang Yu; Pengfei Jiang; Lu Xu; Long Wu; Mingsheng Chen; Yong Zhang; Jianlong Zhang; Xu Yang
• Keywords: Fourier single-pixel imaging; online modulation pattern binarization; deep learning; 0103 physical sciences; deep learning; Applied optics. Photonics; Fourier single-pixel imaging; online modulation pattern binarization; 01 natural sciences; TA1501-1820

Down-sampling Fourier single-pixel imaging is typically achieved by truncating the Fourier spectrum, where exclusively the low-frequency Fourier coefficients are extracted while discarding the high-frequency components. However, the truncation of the Fourier spectrum can lead to an undesired ringing effect in the reconstructed result. Moreover, the original Fourier single-pixel imaging necessitated grayscale Fourier basis patterns for illumination. This requirement limits imaging speed because digital micromirror devices (DMDs) generate grayscale patterns at a lower refresh rate. In order to solve the above problem, a fast and high-quality Fourier single-pixel imaging reconstruction method is proposed in the paper. In the method, the threshold binarization of the Fourier base pattern is performed online to improve the DMD refresh rate, and the reconstruction quality of Fourier single-pixel imaging at a low-sampling rate is improved by generating an adversarial network. This method enables fast reconstruction of target images with higher quality despite low-sampling rates. Compared with conventional Fourier single-pixel imaging, numerical simulation and experimentation demonstrate the effectiveness of the proposed method. Notably, this method is particularly significant for fast Fourier single-pixel imaging applications.