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CVPR
2010
IEEE

A Spatially Varying PSF-based Prior for Alpha Matting

13 years 11 months ago
A Spatially Varying PSF-based Prior for Alpha Matting
In this paper we considerably improve on a state-of-theart alpha matting approach by incorporating a new prior which is based on the image formation process. In particular, we model the prior probability of an alpha matte as the convolution of a high-resolution binary segmentation with the spatially varying point spread function (PSF) of the camera. Our main contribution is a new and efficient deconvolution approach that recovers the prior model, given an approximate alpha matte. By assuming that the PSF is a kernel with a single peak, we are able to recover the binary segmentation with an MRF-based approach, which exploits flux and a new way of enforcing connectivity. The spatially varying PSF is obtained via a partitioning of the image into regions of similar defocus. Incorporating our new prior model into a state-of-the-art matting technique produces results that outperform all competitors, which we confirm using a publicly available benchmark.
Christoph Rhemann, Carsten Rother, Pushmeet Kohli,
Added 08 Apr 2010
Updated 14 May 2010
Type Conference
Year 2010
Where CVPR
Authors Christoph Rhemann, Carsten Rother, Pushmeet Kohli, Margrit Gelautz
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