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Pseudo-random spread spectrum photon counting (PSSPC) is a well-established technique for three-dimensional (3D) imaging. Based on the pseudo-random spread spectrum photon counting system, a fast imaging technique that is able to accurately recover multiple depths at individual pixels is presented. Firstly, a pre-filtering algorithm is used to denoise the original data. Then the accelerated Richardson-Lucy iterative deconvolution algorithm is introduced. The method is based on the principles of vector extrapolation and does not require the minimization of a cost function. For multi-depth estimation in the presence of moderate background light, we experimentally demonstrate that our imaging technique outperforms the existing method. We have successfully improved the range resolution from 21cm to 8cm, thus breaking the Full Width at Half-Maximum (FWHM) resolution limit. The separation Root Mean Square Error (RMSE) has been reduced to 3.82cm by the proposed method for the surface-to-surface separation of 8cm. This is a factor of 4 improvement over the conventional method for multi-depth recovery. Also, our imager has achieved 0.5cm lateral resolution by distinguishing two squares closely placed 0.5cm apart from each other.

As the polarization characteristics are the physical property determined by the material itself, its corresponding polarization image contains abundant target’s information. Using polarization information to identify the target is always a hot research topic in the field of the target detection. Active polarization imaging has more advantages compared with passive polarization imaging because of its high signal-to-noise ratio and good controllability. In this paper, based on the detailed analysis of the theory of the distribution of polarization Fresnel reflectance ratio, a kind of active polarization imaging method is proposed with detecting the polarization Fresnel ratio of the surface of the object. The proposed method adopts two kind of polarization light with orthogonal polarization direction at the light emission part to exposure to the target scenario alternately. Then two cameras side-by-side at the detecting part respectively equipped with two orthogonal polarization direction filters to capture the polarization images. Meanwhile, the detectors are placed in different detecting direction to acquire the polarization imaging with active polarization light source illuminating. Finally, with transmitting the data to the calculating center, optical constants can be recovered from the polarization data by the optimization fitting technique. Because the materials of target’s surface are different, the corresponding optical constants are different. Then the purpose of discriminating the targets with different materials is achieved. The simulated and actual measured experiments are explored to verify the effectiveness of the proposed method. Simulation experiment shows it is not only scientific but also more convenient and effective in that the proposed method can distinguish the different materials using the calculated optical constants. The actual measured data further shows that the method is able to do better in recover optical constants of targets, especially in the distinction between metal and dielectric materials. Furthermore, the system has great application prospect in the field of target detection and camouflage recognition with its simple structure and practicability.