The coded aperture correlation holography (COACH) is a powerful three-dimensional imaging technique. However, the conventional COACH method can only restore the three-dimensional images of the samples under test, but cannot specify the physical characteristics. We propose a full-dimensional measurement method based on the polarized coded aperture correlation holography. Specifically, the dynamic phase and geometric phase distributions can be separated from two holograms associated with the horizontal and vertical polarization components, then the Stokes parameters, surface topography and reflectivity can be calculated simultaneously. This method achieves the same spatial resolution for the two terms, which greatly improves the reliability and practicability with respect to conventional measurement methods.
Interferenceless coded aperture correlation holography (I-COACH) was recently introduced for recording incoherent holograms without two-wave interference. In I-COACH, the light radiated from an object is modulated by a pseudo-randomly-coded phase mask and recorded as a hologram by a digital camera without interfering with any other beams. The image reconstruction is conducted by correlating the object hologram with the point spread hologram. However, the image reconstructed by the conventional correlation algorithm suffers from serious background noise, which leads to poor imaging quality. In this work, via an effective combination of the speckle correlation and neural network, we propose a high-quality reconstruction strategy based on physics-informed deep learning. Specifically, this method takes the autocorrelation of the speckle image as the input of the network, and switches from establishing a direct mapping between the object and the image into a mapping between the autocorrelations of the two. This method improves the interpretability of neural networks through prior physics knowledge, thereby remedying the data dependence and computational cost. In addition, once a final model is obtained, the image reconstruction can be completed by one camera exposure. Experimental results demonstrate that the background noise can be effectively suppressed, and the resolution of the reconstructed images can be enhanced by three times.
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