An improved image reconstruction method for optical intensity correlation Imaging

• Improved method of Prior Information Optimization is proposed and verified by simulation and experiment.
• Improvements are based on estimated intensity distribution model and noise distribution of the object.
• The method can reduce ambiguous images and accelerate the phase retrieval process.
• Object image is better reconstructed with improved method in low SNR condition than previous methods.
• The PIO method works well for deep space object identifications.

The intensity correlation imaging method is a novel kind of interference imaging and it has favorable prospects in deep space recognition. However, restricted by the low detecting signal-to-noise ratio (SNR), it's usually very difficult to obtain high-quality image of deep space object like high-Earth-orbit (HEO) satellite with existing phase retrieval methods. In this paper, based on the priori intensity statistical distribution model of the object and characteristics of measurement noise distribution, an improved method of Prior Information Optimization (PIO) is proposed to reduce the ambiguous images and accelerate the phase retrieval procedure thus realizing fine image reconstruction. As the simulations and experiments show, compared to previous methods, our method could acquire higher-resolution images with less error in low SNR condition.