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Proceedings Paper

Performance analysis of the two-state signal-dependent rank order mean filter
Author(s): Michael Scott Moore; Sanjit K. Mitra
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Paper Abstract

One well-studied image processing task is the removal of impulse noise from images. Impulse noise can be introduced during image capture, during transmission, or during storage. The signal-dependent rank order mean (SD-ROM) filter has been shown to be effective at removing impulses from 2-D scalar- valued signals. Excellent results were presented for both a two-state and a multi-state version of the filter. The two- state SD-ROM filter relies on the selection of a set of threshold values. In this paper, we examine the performance of the algorithm with respect to the thresholds. We take three different approaches. First, we discuss the performance of the algorithm with respect to its root signals. Second, we present a probabilistic model for the SD-ROM filter. This model characterizes the performance of the algorithm in terms of the probability of detecting a corrupted pixel while avoiding uncorrupted pixels. Finally, we apply the insight gained from the root signal analysis and the statistical model to optimized thresholds found using a computerized search algorithm for a large number of images and noise conditions.

Paper Details

Date Published: 5 March 1999
PDF: 11 pages
Proc. SPIE 3646, Nonlinear Image Processing X, (5 March 1999); doi: 10.1117/12.341102
Show Author Affiliations
Michael Scott Moore, Univ. of California/Santa Barbara (United States)
Sanjit K. Mitra, Univ. of California/Santa Barbara (United States)


Published in SPIE Proceedings Vol. 3646:
Nonlinear Image Processing X
Edward R. Dougherty; Jaakko T. Astola, Editor(s)

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