Abstract
This paper describes a cascadic image restoration method which at each level applies a two-way alternating denoising and deblurring procedure. Denoising is carried out with a wavelet transform, which also provides an estimate of the noise-level. The latter is used to determine a suitable regularization parameter for the Krylov subspace iterative deblurring method. The cascadic multilevel method proceed from coarse to fine image resolution, using suitable restriction and prolongation operators. The choice of the latter is critical for the performance of the multilevel method. We introduce a special deblurring prolongation procedure based on TV regularization. Computed examples demonstrate the effectiveness of the method proposed for determining image restorations of high quality.
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Morigi, S., Reichel, L., Sgallari, F. (2013). A Cascadic Alternating Krylov Subspace Image Restoration Method. In: Kuijper, A., Bredies, K., Pock, T., Bischof, H. (eds) Scale Space and Variational Methods in Computer Vision. SSVM 2013. Lecture Notes in Computer Science, vol 7893. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38267-3_9
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DOI: https://doi.org/10.1007/978-3-642-38267-3_9
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