New Estimate for the Redundancy of Natural Images
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1
Max Planck Institute for Biological Cybernetics, NWG Bethge, Germany
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2
Max Planck Institute for Biological Cybernetics, Computational Vision and Neuroscience, Germany
The light intensities of natural images exhibit a high degree of redundancy. Knowing the exact amount of their statistical dependencies is important for biological vision as well as compression and coding applications but estimating the total amount of redundancy, the multi-information, is intrinsically hard. The conventional approach for estimating the redundancy per pixel is to estimate the multi-information for patches of increasing sizes and divide by the number of pixels. Here, we show that the limiting value of this sequence---the multi-information rate---can be better estimated by another limiting process based on measuring the mutual information between a pixel and a causal neighborhood of increasing size around it. We explain the theoretical relationship of the two methods and compare their performance on natural images. While both methods provide a lower bound on the multi-information rate, the mutual information based sequence converges much faster to the multi-information rate than the conventional method does. In this way we can provide improved estimates of the multi-information rate of natural images and a better understanding its underlying spatial structure. In addition, we will present work in progress on hierarchical model architectures that has led to further improvements of this lower bound.
Keywords:
computational neuroscience
Conference:
Bernstein Conference on Computational Neuroscience, Berlin, Germany, 27 Sep - 1 Oct, 2010.
Presentation Type:
Presentation
Topic:
Bernstein Conference on Computational Neuroscience
Citation:
Hosseini
R,
Bethge
M and
Sinz
F
(2010). New Estimate for the Redundancy of Natural Images.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference on Computational Neuroscience.
doi: 10.3389/conf.fncom.2010.51.00006
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Received:
08 Sep 2010;
Published Online:
22 Sep 2010.
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Correspondence:
Dr. Reshad Hosseini, Max Planck Institute for Biological Cybernetics, NWG Bethge, Tubingen, Germany, hosseini@tuebingen.mpg.de