83‐2: Deep Learning‐Based Self‐Interference Incoherent Digital Holography Encoding for Optical Reconstruction

We propose a self‐interference incoherent holography encoding method for enhancing the optical reconstruction performance using deep learning. Self‐interference incoherent digital holography records complex holograms under incoherent illumination conditions. However, conventional optical reconstruction of self‐interference incoherent digital holography is conducted by phase‐only modulation or amplitude‐only modulation. Considering non‐linear representation ability of deep neural networks, we utilize the multi‐layer perceptron as a non‐linear phase mapping function. We design the optimization pipeline to find the phase encoding for phase‐only holographic displays and, an optical demonstration of the proposed phase encoding method is presented.