Learning type of median and mean hybrid filters and a synthesis of its learning signal
Mitsuhiko Meguro, Akira Taguchi, Nozomu Hamada · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1998
We have already proposed the learning type of median and mean hybrid (LMMH) filters which have the desirable properties of both linear filter and nonlinear filters. The LMMH filters are designed by using LMS algorithm, therefore, both the noisy signal and its original signal are required when learning of those. We call the pair of images (i.e. noisy image and its original image) the learning signals. Although the original signal of the noisy image is not given in the practical application. In this paper, we propose a novel making method of learning signals for LMMH filters. In this method, we extract the signal information from the noisy signal and synthesize learning signals by using the information. In the simulations, the new learning signals obtained by the proposed method are shown to be effective for LMMH filters' learning.