New type of modified trimmed mean filter

Wen-Rong Wu*, Amlan Kundu

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations

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 [1]. 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 pre-selected 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) [3-5], 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.

Original languageEnglish
Pages (from-to)13-23
Number of pages11
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume1451
DOIs
StatePublished - 1 Feb 1991
EventNonlinear Image Processing II - San Jose, CA, USA
Duration: 28 Feb 19911 Mar 1991

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