Yinran Shen

Fourier single-pixel imaging (FSI) takes full advantage of the high modulation speed of digital micromirror devices by applying upsampling and spatial dithering to binarize grayscale Fourier patterns, thereby achieving efficient imaging. However, the upsampling process of patterns sacrifices spatial resolution. Here, we propose a binarization method for FSI that enhances reconstructed image quality without the need for upsampling.

Binary patterns are used in fast Fourier single-pixel imaging (FSI) technology to increase the imaging speed at the expense of spatial resolution or image quality. In this Letter, we propose a method for optimizing the image quality-speed trade-off that is informed by physical principles and driven by data from simulations. To compensate for the quantization error induced by binary dithering, convolution kernels are proposed and optimized for both low and high spatial frequencies.