Motion estimation using higher-order statistics
The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimating motion even for small regions or blocks. Using higher than second-order statistics is appropriate in case the image sequence is severely corrupted by additive Gaussi...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 1996 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/1559 |
| Acceso en línea: | https://hdl.handle.net/2117/1559 |
| Access Level: | acceso abierto |
| Palabra clave: | Random noise theory Motion Image processing Additive Gaussian noise Displaced frame difference Fourth-order cost function Higher order statistics Image segmentation Image sequences Mean kurtosis Mean square error Motion estimation Imatges -- Processament -- Matemàtica Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal |
| Sumario: | The objective of this paper is to introduce a fourth-order cost function of the displaced frame difference (DFD) capable of estimating motion even for small regions or blocks. Using higher than second-order statistics is appropriate in case the image sequence is severely corrupted by additive Gaussian noise. Some results are presented and compared to those obtained from the mean kurtosis and the mean square error of the DFD. |
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