New type of modified trimmed mean filter
Wen-Rong Wu, Amlan Kundu · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
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.