Performance Analysis of the Two-State Signal-Dependent Rank Order Mean Filter

Michael S. Moore and Sanjit K.Mitra
Department of Electrical and Computer Engineering
University of California, Santa Barbara
Santa Barbara, CA93106 USA


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 t removing impulses from 2-D scalar-valued signals. Excellent results were presented for both two-state and multi-state version of the filter. The two-state SD-ROM filter relies on the selection of 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 probabilistic model for the SD-ROM filter. This model characterizes the performance of the algorithm in terms of the probability of detecting corrupted pixel while voiding uncorrupted pixels. Finally, we apply the insight gained from the root signal analysis and the statistical model to optimized thresholds found using computerized search algorithm for large number of images and noise conditions.
[PDF] [BibTex]
Michael S. Moore and Sanjit K. Mitra,
SPIE Nonlinear Image Processing X, vol. 3646, pp. 56-66, San Jose, CA, Jan. 1999.
Node ID: 291 , DB ID: 88 , Lab: IPL , Target: Proceedings
Subject: [IPL] « Look up more