In this paper, a new filter, η - LM, which is based on Levenberg-Marquardt Artificial Neural Networks, is proposed for the impulsive noise suppression from highly distorted images. The η - LM uses Anderson-Darling goodness-of-fit test in order to find corrupted pixels more accurately. The extensive simulation results show that the proposed filter achieves a superior performance to the other filters mentioned in this paper in the cases of being effective in detail preservation and noise suppression, especially when the noise density is very high. © Springer-Verlag Berlin Heidelberg 2005.
CITATION STYLE
Çivicioǧlu, P. (2005). Using LM artificial neural networks and η-closest-pixels for impulsive noise suppression from highly corrupted images. In Lecture Notes in Computer Science (Vol. 3497, pp. 679–684). https://doi.org/10.1007/11427445_110
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