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A. Asano, K. Itoh, and Y. Ichioka,
Optimization of the weighted median filter by learning
Opt. Lett., 16, 3, 168-170 (1991).


The weighted median filter (WMF) is a generalization of the median filter. The WMF is more effective for image processing than the conventional. However, the design of the parameters of the WMF is a difficult problem. In this letter, a novel method of optimizing the WMF is proposed. This method utilizes a close relation between the nonrecursive WMF and the feed-forward neural network with shift-invariant weight coefficients. The optimization problem of the WMF results in the learning of the interconnection weights of the network.