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Images and Benford's Law

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Abstract

Benford's law had been proposed in the past as a way to modelize the probability distribution of the first digit in a set of natural numbers. We show in this paper that the magnitude of the gradient of an image obeys this law. We show, experimentally, that this also applies for the laplacian pyramid code. This yields to the field of entropy based coding which takes advantage of the a priori information about the probability of any symbol in the signal.

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Authors and Affiliations

  1. Laboratoire Reconnaissance de Formes et Vision, INSA Lyon, France

    Jean-Michel Jolion

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  1. Jean-Michel Jolion
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Jolion, JM. Images and Benford's Law. Journal of Mathematical Imaging and Vision 14, 73–81 (2001). https://doi.org/10.1023/A:1008363415314

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  • DOI: https://doi.org/10.1023/A:1008363415314

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