Fast Fourier single-pixel imaging based on Sierra-Lite dithering algorithm

The single-pixel imaging (SPI) technique is able to capture two-dimensional (2D) images without conventional array sensors by using a photodiode. As a novel scheme, Fourier single-pixel imaging (FSI) has been proven capable of reconstructing high-quality images. Due to the fact that the Fourier basis patterns (also known as grayscale sinusoidal patterns) cannot be well displayed on the digital micromirror device (DMD), a fast FSI system is proposed to solve this problem by binarizing Fourier pattern through a dithering algorithm. However, the traditional dithering algorithm leads to low quality as the extra noise is inevitably induced in the reconstructed images. In this paper, we report a better dithering algorithm to binarize Fourier pattern, which utilizes the Sierra-Lite kernel function by a serpentine scanning method. Numerical simulation and experiment demonstrate that the proposed algorithm is able to achieve higher quality under different sampling ratios.