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Blind Correction of Optical Aberrations

  • Christian J. Schuler
  • Michael Hirsch
  • Stefan Harmeling
  • Bernhard Schölkopf
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7574)

Abstract

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.

Keywords

Graphic Processing Unit Point Spread Function Chromatic Aberration Blind Deconvolution Optical Aberration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Christian J. Schuler
    • 1
  • Michael Hirsch
    • 1
  • Stefan Harmeling
    • 1
  • Bernhard Schölkopf
    • 1
  1. 1.Max Planck Institute for Intelligent SystemsTübingenGermany

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