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Proceedings Paper

Practical algorithmic probability: an image inpainting example
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Paper Abstract

Possibility of practical application of algorithmic probability is analyzed on an example of image inpainting problem that precisely corresponds to the prediction problem. Such consideration is fruitful both for the theory of universal prediction and practical image inpaiting methods. Efficient application of algorithmic probability implies that its computation is essentially optimized for some specific data representation. In this paper, we considered one image representation, namely spectral representation, for which an image inpainting algorithm is proposed based on the spectrum entropy criterion. This algorithm showed promising results in spite of very simple representation. The same approach can be used for introducing ALP-based criterion for more powerful image representations.

Paper Details

Date Published: 24 December 2013
PDF: 5 pages
Proc. SPIE 9067, Sixth International Conference on Machine Vision (ICMV 2013), 906719 (24 December 2013); doi: 10.1117/12.2051405
Show Author Affiliations
Alexey Potapov, National Research Univ. of Information Technology (Russian Federation)
AIDEUS (Russian Federation)
Oleg Scherbakov, National Research Univ. of Information Technology (Russian Federation)
Innokentii Zhdanov, National Research Univ. of Information Technology (Russian Federation)


Published in SPIE Proceedings Vol. 9067:
Sixth International Conference on Machine Vision (ICMV 2013)
Branislav Vuksanovic; Antanas Verikas; Jianhong Zhou, Editor(s)

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