Robust All-in-Focus Super-Resolution for Focal Stack Photography
We present an unconventional image super-resolution algorithm targeting focal stack images. Contrary to previous works, which align multiple images with sub-pixel accuracy for image super-resolution, we analyze the correlation among the differently focused narrow depth-of-field images in a focal sta...
| Veröffentlicht in: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 25(2016), 4 vom: 02. Apr., Seite 1887-97 |
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| Format: | Online-Aufsatz |
| Sprache: | English |
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2016
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on image processing : a publication of the IEEE Signal Processing Society |
| Schlagworte: | Journal Article |
| Zusammenfassung: | We present an unconventional image super-resolution algorithm targeting focal stack images. Contrary to previous works, which align multiple images with sub-pixel accuracy for image super-resolution, we analyze the correlation among the differently focused narrow depth-of-field images in a focal stack to infer high-resolution details for image super-resolution. In order to accurately model the defocus kernels at different depths, we use a cubic interpolation to parameterize the projection of defocus kernels, and apply the radon transform to accurately reconstruct the defocus kernels at arbitrary depth. In the image super-resolution, we utilize the multi-image deconvolution method with a l1 -norm regularization to suppress noise and ringing artifacts. We have also extended the depth-of-field of our inputs to produce an all-in-focus super-resolution image. The effectiveness of our algorithm is demonstrated with the quantitative analysis using synthetic examples and the qualitative analysis using real-world examples |
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| Beschreibung: | Date Completed 20.07.2016 Date Revised 14.07.2016 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
| ISSN: | 1941-0042 |
| DOI: | 10.1109/TIP.2016.2523419 |