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Estimating Radiometric Response Functions from Image Noise Variance

  • Jun Takamatsu
  • Yasuyuki Matsushita
  • Katsushi Ikeuchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5305)

Abstract

We propose a method for estimating radiometric response functions from observation of image noise variance, not profile of its distribution. The relationship between radiance intensity and noise variance is affine, but due to the non-linearity of response functions, this affinity is not maintained in the observation domain. We use the non-affinity relationship between the observed intensity and noise variance to estimate radiometric response functions. In addition, we theoretically derive how the response function alters the intensity-variance relationship. Since our method uses noise variance as input, it is fundamentally robust against noise. Unlike prior approaches, our method does not require images taken with different and known exposures. Real-world experiments demonstrate the effectiveness of our method.

Keywords

Response Function Noise Variance Shot Noise Noise Distribution Radiometric Calibration 
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 2008

Authors and Affiliations

  • Jun Takamatsu
    • 1
    • 2
  • Yasuyuki Matsushita
    • 3
  • Katsushi Ikeuchi
    • 1
    • 4
  1. 1.Microsoft Institute for Japanese Academic Research Collaboration (MS-IJARC) 
  2. 2.Nara Institute of Science and Technology 
  3. 3.Microsoft Research Asia 
  4. 4.Institute of Industrial Sciencethe University of Tokyo 

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