Image restoration for real-world under-display imaging.
Opt Express
; 29(23): 37820-37834, 2021 Nov 08.
Article
in En
| MEDLINE
| ID: mdl-34808847
ABSTRACT
Under-display imaging technique was recently proposed to enlarge the screen-to-body ratio for full-screen devices. However, existing image restoration algorithms have difficulty generalizing to real-world under-display (UD) images, especially to images containing strong light sources. To address this issue, we propose a novel method for building a synthetic dataset (CalibPSF dataset) and introduce a two-stage neural network to solve the under-display imaging degradation problem. The CalibPSF dataset is generated using the calibrated high dynamic range point spread function (PSF) of the under-display optical system and contains various simulated light sources. The two-stage network solves the color distortion and diffraction degradation in order. We evaluate the performance of our algorithm on our captured real-world test set. Comprehensive experiments demonstrate the superiority of our method in different dynamic range scenes.
Full text:
1
Collection:
01-internacional
Database:
MEDLINE
Language:
En
Journal:
Opt Express
Journal subject:
OFTALMOLOGIA
Year:
2021
Document type:
Article