Collective noise model for focal plane modulated single-pixel imaging

Single-pixel imaging, also known as computational ghost imaging, provides an alternative method to perform imaging in various applications which are difficult for conventional cameras with pixelated detectors, such as multi-wavelength imaging, three-dimensional imaging, and imaging through turbulence. In recent years, many improvements have successfully increased the signal-to-noise ratio of single-pixel imaging systems, showing promise for the engineering feasibility of this technique. However, many of these improvements are based on empirical findings. In this work we perform an investigation of the noise from each system component that affects the quality of the reconstructed image in a single-pixel imaging system based on focal plane modulation. A collective noise model is built to describe the resultant influence of these different noise sources, and numerical simulations are performed to quantify the effect. Experiments have been conducted to verify the model, and the results agree well with the simulations. This work provides a simple yet accurate method for evaluating the performance of a single-pixel imaging system, without having to carry out actual experimental tests.