A new representative criterion for image resampling based on bootstrap and plug in algorithm
| Autor: | Slim M'hiri, Sabra Mabrouk, Faouzi Ghorbel |
|---|---|
| Rok vydání: | 2014 |
| Předmět: |
business.industry
Pattern recognition Probability density function Empirical probability computer.software_genre Representativeness heuristic Image (mathematics) Computer Science::Computer Vision and Pattern Recognition Expectation–maximization algorithm Image scaling Segmentation Plug-in Artificial intelligence business Algorithm computer Mathematics |
| Zdroj: | ICDIP |
| ISSN: | 0277-786X |
| DOI: | 10.1117/12.2064361 |
| Popis: | In this paper we intend to introduce a new representativeness criterion of the Bootstrap sample for images segmentation. Using the plug-in method in order to estimate probability density functions (pdf), we present a robust and stable criterion based on L 2 distance between the estimated probability density from the bootstrap sample and the empirical probability density of the image. This criterion is tested on satellite images. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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