Characterizing the Structure Tensor Using Gamma Distributions

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The structure tensor is a powerful tool describing the local intensity structure of an image or image sequence. In this paper we give a model for the noise distribution of the components of the tensor. In order to do so we have also investigated some properties of the gamma distribution. We show that, given an input image corrupted with Gaussian noise, the noise in the structure tensor can be modeled well by gamma distributions. We apply our model to automatic contrast enhancement of images taken under poor illumination. We show how our noise model can be used for automatic parameter selection in the filtering process, giving powerful results without the need for cumbersome parameter tuning.
Original languageEnglish
Title of host publication Pattern Recognition (ICPR), 2016 23rd International Conference on
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)978-1-5090-4847-2
Publication statusPublished - 2017 Apr 24
Event2016 23rd International Conference on Pattern Recognition (ICPR 2016) - Cancún Center, Cancún, Mexico
Duration: 2016 Dec 42016 Dec 8


Conference2016 23rd International Conference on Pattern Recognition (ICPR 2016)
Abbreviated titleICPR 2016
Internet address

Subject classification (UKÄ)

  • Probability Theory and Statistics
  • Signal Processing
  • Computer Vision and Robotics (Autonomous Systems)

Free keywords

  • Enhancement
  • restoration and filtering
  • Signal, image and video processing
  • Computational photography


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