Pseudo-thermal imaging by using sequential-deviations for real-time image reconstruction

Ghost imaging technologies acquire images through intensity correlation of reference patterns and bucket values. Among them, an interesting method named correspondence imaging can generate positive-negative images by only conditionally averaging reference patterns, but still requires full/over sampling to treat the ensemble average of bucket values as a selection criteria, causing a long acquisition time. Here, we propose a sequential-deviation ghost imaging approach, which can realize real-time reconstructions of positive-negative images with a high image quality close to that of differential ghost imaging. Since it is no longer necessary to compare with the ensemble average, this method can improve the real-time performance. An explanation of its essence is also given here. Both simulation and experimental results have demonstrated the feasibility of this technique. This work may complement the theory of ghost imaging.