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Monday 25 February 2008, 11:15-12:15
Image superresolution
- đ¤ Speaker: Shin-Ichi Maeda
- đ Date & Time: Monday 25 February 2008, 11:15 - 12:15
- đ Venue: TCM Seminar Room, Cavendish Laboratory, Department of Physics
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David MacKay
Abstract
The goal of superresolution is to generate a high-resolution image by integrating low-resolution degraded observed images. We propose a Bayesian approach whose prior is modeled as a compound Gaussian Markov random field (MRF). This approach is advantageous in preserving discontinuity in the original image, in comparison to the existing single-layer Gaussian MRF models. To perform the computation efficiently, we introduce a variatonal EM algorithm.
Series This talk is part of the Machine Learning Journal Club series.
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