Bipolar compressive ghost imaging method to improve imaging quality

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Abstract

Compressive ghost imaging (CGI) can effectively reduce the number of measurements required for ghost imaging reconstruction. In most cases, however, when using illumination patterns as measurement matrices, CGI has not demonstrated the ability to reconstruct high-quality images at an ultra-low sampling rate as perfect as claimed by compressive sensing theory. According to our analysis, the reason is that the non-negative nature of light intensity causes measurement matrix in compressive ghost imaging to be inconsistent with the essential requirements of good measurement matrix in compressive sensing theory, leading to low reconstruction quality. Aiming at this point, we propose a bipolar compressive ghost imaging method to improve the reconstruction quality of ghost imaging. The validity of the proposed method is proven by simulations and experiments.

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