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Maximum likelihood extension for non-circulant deconvolution

Autor Portilla, Javier
Palabras clave Maximum likelihood extension
Boundary artifacts
Non-circulant deconvolution
Image restoration
Fecha de publicación 27-oct-2014
EditorInstitute of Electrical and Electronics Engineers
Citación IEEE ICIP (2014)
ResumenDirectly applying circular de-convolution to real-world blurred images usually results in boundary artifacts. Classic boundary extension techniques fail to provide likely results, in terms of a circular boundary-condition observation model. Boundary reflection gives raise to non-smooth features, especially when oblique oriented features encounter the image boundaries. Tapering the boundaries of the image support, or similar strategies (like constrained diffusion), provides smoothness on the toroidal support; however this does not guarantee consistency with the spectral properties of the blur (in particular, to its zeros). Here we propose a simple, yet effective, model-derived method for extending real-world blurred images, so that they become likely in terms of a Gaussian circular boundary-condition observation model. We achieve artifact-free results, even under highly unfavorable conditions, when other methods fail.
Descripción The International Conference on Image Processing, Paris, France, October 27-30 2014
URI http://hdl.handle.net/10261/114812
Aparece en las colecciones: (CFMAC-IO) Comunicaciones congresos
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