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JMIV
2011

Direct Sparse Deblurring

8 years 7 months ago
Direct Sparse Deblurring
We propose a deblurring algorithm that explicitly takes into account the sparse characteristics of natural images and does not entail solving a numerically ill-conditioned backward-diffusion. The key observation is that the sparse coefficients that encode a given image with respect to an over-complete basis are the same that encode a blurred version of the image with respect to a modified basis. Following an “analysis-by-synthesis” approach, an explicit generative model is used to compute a sparse representation of the blurred image, and the coefficients of which are used to combine elements of the original basis to yield a restored image. We compare our algorithm against the state of the art in variational methods as well as wavelet-based algorithms.
Yifei Lou, Andrea L. Bertozzi, Stefano Soatto
Added 14 May 2011
Updated 14 May 2011
Type Journal
Year 2011
Where JMIV
Authors Yifei Lou, Andrea L. Bertozzi, Stefano Soatto
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