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Title: Iterative truncated arithmetic mean filter and its properties
Authors: Jiang, Xudong
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
Issue Date: 2011
Source: Jiang, X. (2011). Iterative truncated arithmetic mean filter and its properties. IEEE transactions on image processing, 21(4), 1537-1547.
Series/Report no.: IEEE transactions on image processing
Abstract: The arithmetic mean and the order statistical median are two fundamental operations in signal and image processing. They have their own merits and limitations in noise attenuation and image structure preservation. This paper proposes an iterative algorithm that truncates the extreme values of samples in the filter window to a dynamic threshold. The resulting nonlinear filter shows some merits of both the fundamental operations. Some dynamic truncation thresholds are proposed that guarantee the filter output, starting from the mean, to approach the median of the input samples. As a by-product, this paper unveils some statistics of a finite data set as the upper bounds of the deviation of the median from the mean. Some stopping criteria are suggested to facilitate edge preservation and noise attenuation for both the long- and short-tailed distributions. Although the proposed iterative truncated mean (ITM) algorithm is not aimed at the median, it offers a way to estimate the median by simple arithmetic computing. Some properties of the ITM filters are analyzed and experimentally verified on synthetic data and real images.
ISSN: 1057-7149
DOI: 10.1109/TIP.2011.2172805
Rights: © 2011 IEEE
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:EEE Journal Articles

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