Abstract
In this chapter, we present examples of image restoration using periodic frames. Images to be restored were degraded by blurring, aggravated by random noise and random loss of significant number of pixels. The images are transformed by periodic frames designed in Sects. 17.2 and 17.4, which are extended to the 2D setting in a standard tensor product way. In the presented experiments, performances of different tight and semi-tight frames are compared between each other in identical conditions.
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References
T. Goldstein, S. Osher, The split Bregman method for L1-regularized problems. SIAM J. Imaging Sci. 2(2), 323–343 (2009)
H. Ji, Z. Shen, Y. Xu, Wavelet based restoration of images with missing or damaged pixels. East Asian J. Appl. Math. 1(2), 108–131 (2011)
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© 2014 Springer Science+Business Media Dordrecht
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Averbuch, A.Z., Neittaanmaki, P., Zheludev, V.A. (2014). Application of Periodic Frames to Image Restoration. In: Spline and Spline Wavelet Methods with Applications to Signal and Image Processing. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-8926-4_18
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DOI: https://doi.org/10.1007/978-94-017-8926-4_18
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Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-017-8925-7
Online ISBN: 978-94-017-8926-4
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