Fresnel Lens Imaging With Post-Capture Image Processing

Artem Nikonorov, Roman Skidanov, Vladimir Fursov, Maksim Petrov, Sergey Bibikov, Yuriy Yuzifovich; Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2015, pp. 33-41


This paper describes a unified approach to correct optical distortions in images formed by a Fresnel lens with computational post-processing that opens up new opportunities to use Fresnel lenses in lightweight and inexpensive computer vision devices. Traditional methods of aberration correction do not address artifacts introduced by a Fresnel lens in a systematic way and thus fail to deliver image quality acceptable for generalpurpose color imaging. In our approach, the image is restored using three steps: first, by deblurring the base color channel, then by sharpening other two channels, and finally by applying color correction. Deblurring and sharpening remove significant chromatic aberration and are similar to the restoration technique used for images formed by simple refraction lenses. Color correction stage removes strong color shift caused by energy redistribution between diffraction orders of Fresnel lens. This post-capture processing was tested on real images formed by a four-step approximation of the Fresnel lens manufactured in our optics laboratory.

Related Material

author = {Nikonorov, Artem and Skidanov, Roman and Fursov, Vladimir and Petrov, Maksim and Bibikov, Sergey and Yuzifovich, Yuriy},
title = {Fresnel Lens Imaging With Post-Capture Image Processing},
booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2015}