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Blind Correction of Optical Aberrations

2012

Conference Paper

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Camera lenses are a critical component of optical imaging systems, and lens imperfections compromise image quality. While traditionally, sophisticated lens design and quality control aim at limiting optical aberrations, recent works [1,2,3] promote the correction of optical flaws by computational means. These approaches rely on elaborate measurement procedures to characterize an optical system, and perform image correction by non-blind deconvolution. In this paper, we present a method that utilizes physically plausible assumptions to estimate non-stationary lens aberrations blindly, and thus can correct images without knowledge of specifics of camera and lens. The blur estimation features a novel preconditioning step that enables fast deconvolution. We obtain results that are competitive with state-of-the-art non-blind approaches.

Author(s): Schuler, CJ. and Hirsch, M. and Harmeling, S. and Schölkopf, B.
Book Title: Computer Vision - ECCV 2012, LNCS Vol. 7574
Pages: 187-200
Year: 2012
Day: 0
Editors: A Fitzgibbon, S Lazebnik, P Perona, Y Sato, and C Schmid
Publisher: Springer

Department(s): Empirical Inference
Research Project(s): Computational Imaging
Bibtex Type: Conference Paper (inproceedings)

Address: Berlin, Germany
Digital: 0
DOI: 10.1007/978-3-642-33712-3_14
Event Name: 12th IEEE European Conference on Computer Vision, ECCV 2012
Event Place: Florence, Italy
ISBN: 978-3-642-33711-6

Links: PDF
Web

BibTex

@inproceedings{SchulerHHS2012,
  title = {Blind Correction of Optical Aberrations},
  author = {Schuler, CJ. and Hirsch, M. and Harmeling, S. and Sch{\"o}lkopf, B.},
  booktitle = {Computer Vision - ECCV 2012, LNCS Vol. 7574},
  pages = {187-200},
  editors = {A Fitzgibbon, S Lazebnik, P Perona, Y Sato, and C Schmid},
  publisher = {Springer},
  address = {Berlin, Germany},
  year = {2012}
}