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Image Enhancement Using Calibrated Lens Simulations

  • Yichang Shih
  • Brian Guenter
  • Neel Joshi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7575)

Abstract

All lenses have optical aberrations which reduce image sharpness. These aberrations can be reduced by deconvolving an image using the lens point spread function (PSF). However, fully measuring a PSF is laborious and prohibitive. Alternatively, one can simulate the PSF if the lens model is known. However, due to manufacturing tolerances lenses differ subtly from their models, so often a simulated PSF is a poor match to measured data. We present an algorithm that uses a PSF measurement at a single depth to calibrate the nominal lens model to the measured PSF. The calibrated model can then be used to compute the PSF for any desired setting of lens parameters for any scene depth, without additional measurements or calibration. The calibrated model gives deconvolution results comparable to measurement but is much more compact and require hundreds of times fewer calibration images.

Keywords

Point Spread Function Image Enhancement Chromatic Aberration Dispersion Function Lens Model 
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

  • Yichang Shih
    • 1
    • 2
  • Brian Guenter
    • 1
  • Neel Joshi
    • 1
  1. 1.Microsoft ResearchUSA
  2. 2.MIT CSAILUSA

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