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Proceedings Paper

New type of modified trimmed mean filter
Author(s): Wen-Rong Wu; Amlan Kundu
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Paper Abstract

In this paper, we propose a new type of modified trimmed mean (MTM) filter for image smoothing. The MTM filter was first proposed by Lee and Kassam. The filter is designed to remedy the problem of edge blurring resulted by a mean filtering. The idea is to perform the averaging operation on some selected samples inside a window. A data sample is selected if its value falls into the range of (m - q, m + q) where m is a value calculated from the data samples and q is a preselected threshold value. Lee et al used the median filter to estimate the m value. Although the MTM filter works well for some images, it cannot preserve the details. This is because the median filter is not a detail preserving filter. In this paper, we propose to replace the median filter by a detail preserving filter, namely multistage median (MSM), for the m value estimation. We call this filter the multistage median based MTM (MSMTM) filter. It is shown that the new MSMTM filter is highly efficient and detail- preserving. By some modification, the MSMTM can also be used to filter the multiplicative noise. Finally, simulations are carried out to evaluate the performance of the filter.

Paper Details

Date Published: 1 April 1991
PDF: 11 pages
Proc. SPIE 1451, Nonlinear Image Processing II, (1 April 1991); doi: 10.1117/12.44312
Show Author Affiliations
Wen-Rong Wu, National Chiao-Tung Univ. (Taiwan)
Amlan Kundu, SUNY/Buffalo (United States)

Published in SPIE Proceedings Vol. 1451:
Nonlinear Image Processing II
Edward R. Dougherty; Gonzalo R. Arce; Charles G. Boncelet Jr., Editor(s)

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