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- Publisher Website: 10.1109/ICCV.2017.352
- Scopus: eid_2-s2.0-85041896287
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Conference Paper: Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction
Title | Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction |
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Authors | |
Issue Date | 2017 |
Citation | Proceedings of the IEEE International Conference on Computer Vision, 2017, v. 2017-October, p. 3268-3276 How to Cite? |
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. |
Persistent Identifier | http://hdl.handle.net/10722/315283 |
ISSN | 2023 SCImago Journal Rankings: 12.263 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Sun, Tiancheng | - |
dc.contributor.author | Peng, Yifan | - |
dc.contributor.author | Heidrich, Wolfgang | - |
dc.date.accessioned | 2022-08-05T10:18:19Z | - |
dc.date.available | 2022-08-05T10:18:19Z | - |
dc.date.issued | 2017 | - |
dc.identifier.citation | Proceedings of the IEEE International Conference on Computer Vision, 2017, v. 2017-October, p. 3268-3276 | - |
dc.identifier.issn | 1550-5499 | - |
dc.identifier.uri | http://hdl.handle.net/10722/315283 | - |
dc.description.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. | - |
dc.language | eng | - |
dc.relation.ispartof | Proceedings of the IEEE International Conference on Computer Vision | - |
dc.title | Revisiting Cross-Channel Information Transfer for Chromatic Aberration Correction | - |
dc.type | Conference_Paper | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1109/ICCV.2017.352 | - |
dc.identifier.scopus | eid_2-s2.0-85041896287 | - |
dc.identifier.volume | 2017-October | - |
dc.identifier.spage | 3268 | - |
dc.identifier.epage | 3276 | - |
dc.identifier.isi | WOS:000425498403035 | - |