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Proceedings Paper

New algorithms for adaptive median filters
Author(s): Hyun Ha Hwang; Richard A. Haddad
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Paper Abstract

We present two robust adaptive median filters with variable window size which are capable of removing a mixture of positive and negative impulse noise while preserving sharpness of an edge. In the first case, we assume that each pixel at (i J ) is corrupted by an impulse with probabilitype independent of other pixels corrupted or not. The impulse corrupted pixel takes on the minimum pixel value smm with probability q or the maximum pixel value mwith probability 1 when the original pixel s is corrupted by a negative or a positive impulse, respectively. Let {x } be the noise corrupted image. Then I e,1 with Pe xii = 1 with 1 The RAMF algorithm is based on a test for the presence of an impulse at the center pixel followed by a test for the detection of residual impulse in the median filter output. In the second model, the noise corrupted pixel is x =s +n1 , where n1 is iid impulsive noise having Laplacian, or Cauchy, or a mixture of Gaussian and Cauchy distributions. The SAMF algorithm in this instance detects the width of the impulse and adjusts the window accordingly until the noise is eliminated. These algorithms were tested on standard images. The RAMF is shown to be supenor to the nonlinear mean L filter[1] while the SAMF is better performing and simpler than [in's adaptive scheme[3].

Paper Details

Date Published: 1 November 1991
PDF: 8 pages
Proc. SPIE 1606, Visual Communications and Image Processing '91: Image Processing, (1 November 1991); doi: 10.1117/12.50402
Show Author Affiliations
Hyun Ha Hwang, Polytechnic Univ. (United States)
Richard A. Haddad, Polytechnic Univ. (United States)


Published in SPIE Proceedings Vol. 1606:
Visual Communications and Image Processing '91: Image Processing
Kou-Hu Tzou; Toshio Koga, Editor(s)

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