IEEE Trans Image Process - Iterative truncated arithmetic mean filter and its properties.

Tópicos

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Resumo

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.

Resumo Limpo

arithmet mean order statist median two fundament oper signal imag process merit limit nois attenu imag structur preserv paper propos iter algorithm truncat extrem valu sampl filter window dynam threshold result nonlinear filter show merit fundament oper dynam truncat threshold propos guarante filter output start mean approach median input sampl byproduct paper unveil statist finit data set upper bound deviat median mean stop criteria suggest facilit edg preserv nois attenu long shorttail distribut although propos iter truncat mean itm algorithm aim median offer way estim median simpl arithmet comput properti itm filter analyz experiment verifi synthet data real imag

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