Abstract The trimmed mean is one of the most common estimators of location for symmetrical distributions, whose effect depends on whether the trim rate matches the proportion of contaminated data. Based on the geometric characteristics of the curve of the trimmed variance function, the authors propose two kinds of adaptive trimmed mean algorithms. The accuracy of the estimators is compared with...

An advanced non-linear cascading filter algorithm for the removal of high density salt and pepper noise from the digital images is proposed. The proposed method consists of two stages. The first stage Decision base Median Filter (DMF) acts as the preliminary noise removal algorithm. The second stage is either Modified Decision Base Partial Trimmed Global Mean Filter (MDBPTGMF) or Modified Decis...

In this paper, we address the design of multichannel L-filters based on marginal data ordering using the Mean-Squared-Error as fidelity criterion. Design procedures subject to the constraints of unbiased or location-invariant estimation or without imposing any constraint are discussed. It is shown by simulations that the proposed multichannel L-filters perform better than other multichannel non...

In this paper, we are proposing an approach to minimize very high density salt and pepper noise through trimmed global mean. The Modified decision based unsymmetrical trimmed median filter tries to remove high density salt and pepper noise by taking the mean value of the elements within the processing window. This algorithm fails if all the elements within the processing window is either ‘0’ or...

Context. Fortunately, the most commonly used in parametric statistics assumptions such as normality, linearity, independence, are not always fulfilled real practice. The main reason for this is appearance of observations data samples that differ from bulk data, a result which sample becomes heterogeneous. application conditions generally accepted estimation procedures, example, mean, entails bi...