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A \(l_1\) norm based image prior combination in multiframe superresolution. (English) Zbl 1426.94057

Summary: We address the multiframe superresolution problem using the variational Bayesian method in this paper. In the variational Bayesian framework, the prior is crucial in transferring the ill-posed reconstruction problem to a well-posed one. We propose a prior combination method based on filter bank and \(l_1\) norm. Multiple filters are used in our prior model, and the corresponding combination coefficient vector can be estimated by the characteristics of the filtered image and noise. Furthermore, the local adaptive coefficients of every filter are more effective in removing noise and preserving image edges. Extensive experiments demonstrate the advantages of the proposed method.

MSC:

94A12 Signal theory (characterization, reconstruction, filtering, etc.)
62H35 Image analysis in multivariate analysis
62F15 Bayesian inference
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