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Non-parametric image super-resolution using multiple images
Gupta, M.D.; Rajaram, S.; Petrovic, N.; Huang, T.S.;
Image Processing, 2005. ICIP 2005. IEEE International Conference on
Volume 2,
11-14 Sept. 2005
Page(s):II
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89-92
Abstract:
In this paper, we present a novel learning based framework for performing super-resolution using multiple images. We model the image as an undirected graphical model over image patches in which the compatibility functions are represented as non-parametric kernel densities which are learnt from training data. The observed images are translation rectified and stitched together onto a high resolution grid and the inference problem reduces to estimating unknown pixels in the grid. We solve the inference problem by using an extended version of the non-parametric belief propagation algorithm. We show experimental results on synthetic digit images and real face images from the ORL face dataset.
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