Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction

Tiancheng Sun, Yifan Peng, Wolfgang Heidrich

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Image aberrations can cause severe degradation in image quality for consumer-level cameras, especially under the current tendency to reduce the complexity of lens designs in order to shrink the overall size of modules. In simplified optical designs, chromatic aberration can be one of the most significant causes for degraded image quality, and it can be quite difficult to remove in post-processing, since it results in strong blurs in at least some of the color channels. In this work, we revisit the pixel-wise similarity between different color channels of the image and accordingly propose a novel algorithm for correcting chromatic aberration based on this cross-channel correlation. In contrast to recent weak prior-based models, ours uses strong pixel-wise fitting and transfer, which lead to significant quality improvements for large chromatic aberrations. Experimental results on both synthetic and real world images captured by different optical systems demonstrate that the chromatic aberration can be significantly reduced using our approach.
Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Computer Vision (ICCV)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages3268-3276
Number of pages9
ISBN (Print)9781538610329
DOIs
StatePublished - Dec 25 2017

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