Practical algorithmic probability: an image inpainting example
| Autor: | Oleg Scherbakov, Innokentii Zhdanov, Alexey Potapov |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Theoretical computer science
business.industry Computation ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Inpainting External Data Representation Image (mathematics) Data visualization Simple (abstract algebra) Computer Science::Computer Vision and Pattern Recognition Algorithmic probability business Representation (mathematics) Mathematics |
| Zdroj: | SPIE Proceedings. |
| ISSN: | 0277-786X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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