Optimal binarization of input images or hologoraphic neural networks

摘要

The optical imp[elemtnation of neural networks using volume holograms for weighted interconnections requires stable phase relation between input channels. This is particularly important for images with variable illumination. One way to solve this problem is to use binary inputs. The simplest binarization is the direct quantization, but this method has a numbr of disadvantages. Error diffusion algorithm is more robust under variable illumination since it keeps the original image characteristics.