Single-pixel Fresnel incoherent correlation holography compressed imaging using a Trumpet network

Abstract

Abstract Fresnel incoherent correlation holography (FINCH) can achieve high-precision and non-scanning 3D imaging. However, as a holographic imaging technology, the huge bandwidth requirements and the amount of holographic data transmitted have always been one of the important factors limiting its application. In addition, the hardware cost of pixel array-based CCD or CMOS imaging is very high under high resolution or specific wavelength conditions. Accordingly, a single-pixel Fresnel incoherent correlation holography (SP-FINCH) compressed imaging method is proposed, which replaces pixel array detector with single-pixel detector and designs a Trumpet network to achieve low-cost and high-resolution imaging. Firstly, a modified FINCH imaging system is constructed and data acquisition is carried out using a single-pixel detector. Secondly, a Trumpet network is constructed to directly map the relationship between one-dimensional sampled data and two-dimensional image in an end-to-end manner. Moreover, by comparing the reconstructed images using neural network with that using commonly used single-pixel reconstruction methods, the results indicate that the proposed SP-FINCH compressed imaging method can significantly improve the quality of image reconstruction at lower sampling rate and achieve imaging without phase-shifting operation. The proposed method has been shown to be feasible and advantageous through numerical simulations and optical experiment results.