Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction

Handle URI:
http://hdl.handle.net/10754/627152
Title:
Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction
Authors:
Sun, Tiancheng; Peng, Yifan; Heidrich, Wolfgang ( 0000-0002-4227-8508 )
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.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program; Visual Computing Center (VCC)
Citation:
Sun T, Peng Y, Heidrich W (2017) Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction. 2017 IEEE International Conference on Computer Vision (ICCV). Available: http://dx.doi.org/10.1109/ICCV.2017.352.
Publisher:
IEEE
Journal:
2017 IEEE International Conference on Computer Vision (ICCV)
Conference/Event name:
16th IEEE International Conference on Computer Vision, ICCV 2017
Issue Date:
25-Dec-2017
DOI:
10.1109/ICCV.2017.352
Type:
Conference Paper
Sponsors:
This work was supported by KAUST baseline funding, as well as a UBC 4YF Doctoral Fellowship. The authors thank Tao Yue, Qiang Fu, and Felix Heide for the help on synthetic results.
Additional Links:
http://ieeexplore.ieee.org/document/8237614/
Appears in Collections:
Conference Papers; Computer Science Program; Visual Computing Center (VCC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorSun, Tianchengen
dc.contributor.authorPeng, Yifanen
dc.contributor.authorHeidrich, Wolfgangen
dc.date.accessioned2018-02-21T06:47:36Z-
dc.date.available2018-02-21T06:47:36Z-
dc.date.issued2017-12-25en
dc.identifier.citationSun T, Peng Y, Heidrich W (2017) Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction. 2017 IEEE International Conference on Computer Vision (ICCV). Available: http://dx.doi.org/10.1109/ICCV.2017.352.en
dc.identifier.doi10.1109/ICCV.2017.352en
dc.identifier.urihttp://hdl.handle.net/10754/627152-
dc.description.abstractImage 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.en
dc.description.sponsorshipThis work was supported by KAUST baseline funding, as well as a UBC 4YF Doctoral Fellowship. The authors thank Tao Yue, Qiang Fu, and Felix Heide for the help on synthetic results.en
dc.publisherIEEEen
dc.relation.urlhttp://ieeexplore.ieee.org/document/8237614/en
dc.rights(c) 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.en
dc.titleRevisiting Cross-Channel Information Transfer for Chromatic Aberration Correctionen
dc.typeConference Paperen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.contributor.departmentVisual Computing Center (VCC)en
dc.identifier.journal2017 IEEE International Conference on Computer Vision (ICCV)en
dc.conference.date2017-10-22 to 2017-10-29en
dc.conference.name16th IEEE International Conference on Computer Vision, ICCV 2017en
dc.conference.locationVenice, ITAen
dc.eprint.versionPost-printen
dc.contributor.institutionIIIS, Tsinghua University, Beijing, , Chinaen
dc.contributor.institutionUniversity of British Columbia, Vancouver, , Canadaen
kaust.authorSun, Tianchengen
kaust.authorPeng, Yifanen
kaust.authorHeidrich, Wolfgangen
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