Learning type of median and mean hybrid filters and a synthesis of its learning signal

Mitsuhiko Meguro; Akira Taguchi; Nozomu Hamada

doi:10.1117/12.304618

6 April 1998 Learning type of median and mean hybrid filters and a synthesis of its learning signal

Mitsuhiko Meguro, Akira Taguchi, Nozomu Hamada

Proceedings Volume 3304, Nonlinear Image Processing IX; (1998) https://doi.org/10.1117/12.304618
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States

Abstract

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.

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Mitsuhiko Meguro, Akira Taguchi, and Nozomu Hamada "Learning type of median and mean hybrid filters and a synthesis of its learning signal", Proc. SPIE 3304, Nonlinear Image Processing IX, (6 April 1998); https://doi.org/10.1117/12.304618

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KEYWORDS

Electronic filtering

Optical filters

Digital filtering

Nonlinear filtering

Image filtering

Finite impulse response filters

Interference (communication)

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