Hybrid Refractive-Diffractive Lens with Reduced Chromatic and Geometric Aberrations and Learned Image Reconstruction.

Autor: Evdokimova VV; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Podlipnov VV; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Ivliev NA; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Petrov MV; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Ganchevskaya SV; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Fursov VA; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Yuzifovich YY; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Stepanenko SO; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Kazanskiy NL; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Nikonorov AV; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia., Skidanov RV; Image Processing Systems Institute of the RAS-Branch of the FSRC 'Crystallography and Photonics' RAS, Molodogvardeiskaya St. 151, Samara 443001, Russia.; Samara National Research University, Moskovskoye Shosse 34, Samara 443086, Russia.
Jazyk: angličtina
Zdroj: Sensors (Basel, Switzerland) [Sensors (Basel)] 2022 Dec 30; Vol. 23 (1). Date of Electronic Publication: 2022 Dec 30.
DOI: 10.3390/s23010415
Abstrakt: In this paper, we present a hybrid refractive-diffractive lens that, when paired with a deep neural network-based image reconstruction, produces high-quality, real-world images with minimal artifacts, reaching a PSNR of 28 dB on the test set. Our diffractive element compensates for the off-axis aberrations of a single refractive element and has reduced chromatic aberrations across the visible light spectrum. We also describe our training set augmentation and novel quality criteria called "false edge level" (FEL), which validates that the neural network produces visually appealing images without artifacts under a wide range of ISO and exposure settings. Our quality criteria (FEL) enabled us to include real scene images without a corresponding ground truth in the training process.
Databáze: MEDLINE
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