In:
Optics Express, Optica Publishing Group, Vol. 31, No. 21 ( 2023-10-09), p. 34609-
Abstract:
This paper proposes a method that utilizes a dual neural network model to address the challenges posed by aberration in the integral imaging microlens array (MLA) and the degradation of 3D image quality. The approach involves a cascaded dual convolutional neural network (CNN) model designed to handle aberration pre-correction and image quality restoration tasks. By training these models end-to-end, the MLA aberration is corrected effectively and the image quality of integral imaging is enhanced. The feasibility of the proposed method is validated through simulations and optical experiments, using an optimized, high-quality pre-corrected element image array (EIA) as the image source for 3D display. The proposed method achieves high-quality integral imaging 3D display by alleviating the contradiction between MLA aberration and 3D image resolution reduction caused by system noise without introducing additional complexity to the display system.
Type of Medium:
Online Resource
ISSN:
1094-4087
Language:
English
Publisher:
Optica Publishing Group
Publication Date:
2023
detail.hit.zdb_id:
1491859-6
