학술논문

Experimental digital Gabor hologram rendering by a model-trained convolutional neural network
Document Type
Working Paper
Source
Subject
Electrical Engineering and Systems Science - Image and Video Processing
Physics - Data Analysis, Statistics and Probability
Physics - Optics
Language
Abstract
Digital hologram rendering can be performed by a convolutional neural network, trained with image pairs calculated by numerical wave propagation from sparse generating images. 512-by-512 pixeldigital Gabor magnitude holograms are successfully estimated from experimental interferograms by a standard UNet trained with 50,000 synthetic image pairs over 70 epochs.