Abstract
Although many filters have been proposed,image denoising is still worth further studying. In this paper, two novel image filters based on canonical piecewise linear networks are presented. They have the advantages of both linear filters and nonlinear filters. The former filter removes noises through the estimation of local structure, while the latter one accomplishes that by approximating the mapping from degraded images to clear images. They can remove noises effectively and preserve the details well. Finally, simulation results are shown to support their effectiveness.
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© 2005 Springer-Verlag Berlin Heidelberg
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Sun, X., Wang, S., Wang, Y. (2005). Two Novel Image Filters Based on Canonical Piecewise Linear Networks. In: Wang, J., Liao, XF., Yi, Z. (eds) Advances in Neural Networks – ISNN 2005. ISNN 2005. Lecture Notes in Computer Science, vol 3497. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11427445_111
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DOI: https://doi.org/10.1007/11427445_111
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25913-8
Online ISBN: 978-3-540-32067-8
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