Phase Imaging through Scattering Media Using Incoherent Light Source

Phase imaging normally employs coherent a light source while an incoherent light source is not preferred due to its random wavefront. Another challenge for practical phase imaging is imaging through scattering media, which scatter the photons in a random manner and lead to seriously distorted images of speckles. Based on the convolutional neural network (CNN), this paper presents an approach for phase imaging through scattering media using an incoherent light source. A CNN was trained and utilized to reconstruct the target images from the captured images of speckles. Similarities of over 90% between the reconstructed images and their target images have been achieved. It was concluded that an incoherent light source can be used as an illumination source for scattering phase imaging with the assistance of deep learning technology. This phase imaging approach with an incoherent light source through scattering media can be used to record the refractive indices of transparent samples, which might lead to its application in biomedical imaging.

Automated summary

This paper presents an approach for phase imaging through scattering media using an incoherent light source, by training a Convolutional Neural Network (CNN) to reconstruct target images from captured speckle images. Over 90% similarities between reconstructed and target images were achieved. It concludes that an incoherent light source can be used for scattering phase imaging with the assistance of deep learning technology.