Blind Optical Aberration Correction by Exploring Geometric and Visual Priors

Tao Yue, Jinli Suo, Jue Wang, Xun Cao, Qionghai Dai; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 1684-1692

Abstract


Optical aberration widely exists in optical imaging systems, especially in consumer-level cameras. In contrast to previous solutions using hardware compensation or pre-calibration, we propose a computational approach for blind aberration removal from a single image, by exploring various geometric and visual priors. The global rotational symmetry allows us to transform the non-uniform degeneration into several uniform ones by the proposed radial splitting and warping technique. Locally, two types of symmetry constraints, i.e. central symmetry and reflection symmetry are defined as geometric priors in central and surrounding regions, respectively. Furthermore, by investigating the visual artifacts of aberration degenerated images captured by consumer-level cameras, the non-uniform distribution of sharpness across color channels and the image lattice is exploited as visual priors, resulting in a novel strategy to utilize the guidance from the sharpest channel and local image regions to improve the overall performance and robustness. Extensive evaluation on both real and synthetic data suggests that the proposed method outperforms the state-of-the-art techniques.

Related Material


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[bibtex]
@InProceedings{Yue_2015_CVPR,
author = {Yue, Tao and Suo, Jinli and Wang, Jue and Cao, Xun and Dai, Qionghai},
title = {Blind Optical Aberration Correction by Exploring Geometric and Visual Priors},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}