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In current research, it is still a hot topic for 3D reconstruction under complex illumination. This paper uses a polarization camera combined with a coding technique to propose a new 3D reconstruction method for polarized ambient light separation. Based on the polarization camera, a specific separation model is established to analyze the relationship between the polarization characteristics of polarized and natural light. Specular reflections were filtered first and then analyzed based on the stocks vector and muller matrix. A specific calculation process was used to calculate different polarization azimuths according to the polarization characteristics, and finally, the polarized light and ambient light were separated. The experimental results show that the use of this polarization camera approach reduces the number of steps required to rotate the polarizer multiple times. This not only reduces the shooting time but also improves the efficiency. Moreover, after separating the ambient light, polarization imaging suppresses the interference of the ambient light, which helps to highlight the complete point cloud image more clearly in the 3D reconstruction. The standard deviation of 3D reconstruction was improved to 0.1675 mm by using this method in indoor and outdoor experiments.

Conventional research in structured light measurements has utilized light intensity as a channel for information. The polarization of light can be used as an additional channel of information. In this paper, a method based on the superposition of multiple polarization states is proposed to encode structured light. By building a polarization model between the color of light and the polarization states, polarized structured light containing phase information is obtained without rotating the polarizer. It is demonstrated that the method improves the waveform quality of stripes and the accuracy of the 3D reconstruction results when measuring highly reflective objects.