Computational-weighted Fourier single-pixel imaging via binary illumination.

Single-pixel imaging has the ability to generate images at nonvisible wavelengths and under low light conditions and thus has received increasing attention in recent years. Fourier single-pixel imaging (FSI) utilizes deterministic basis patterns for illumination to greatly improve the quality of image reconstruction. However, the original FSI based on grayscale Fourier basis illumination patterns is limited by the imaging speed as the digital micro-mirror devices (DMD) used to generate grayscale patterns operate at a low refresh rate. In this paper, a new approach is proposed to increase the imaging speed of DMD-based FSI without reducing the imaging spatial resolution. In this strategy, the grayscale Fourier basis patterns are split into a pair of grayscale patterns based on positive/negative pixel values, which are then decomposed into a cluster of binary basis patterns based on the principle of decimalization to binary. These binary patterns are used to illuminate the imaged object. The resulting detected light intensities multiply the corresponding weighted decomposed coefficients and are summed, and the results can be used to generate the Fourier spectrum for the imaged object. Finally, an inverse Fourier transform is applied to the Fourier spectrum to obtain the object image. The proposed technique is verified by a computational simulation and laboratory experiments. Both static and dynamic imaging experiments are carried out to demonstrate the proposed strategy. 128 × 128 pixels dynamic scenes at a speed of ~9 frames-per-second are captured under 22 KHz projection rate using a DMD. The reported technique accelerates the imaging speed for DMD-based FSI and provides an alternative approach to improve FSI efficiency.