Title
Optimal order statistic filters with coefficient censoring
Abstract
Order statistic (OS) filters are noted for their robust properties for smoothing or estimating signals immersed in noise. The effect of coefficient censoring on the smoothing performance of OS filters is considered. Coefficient censoring can be effected either by adding zero coefficients to an existing filter, or by computing the optimal (MSE) censored coefficients for a set filter span. The second possibility is considered. In both cases, censoring can yield increased robustness and improved edge retention. OS filters in common use which can be interpreted as censored OS filters include the median filter, rank-order filters, and the trimmed mean filters. While optimal censored filters are generally suboptimal relative to optimal uncensored filters, they often yield superior performance for signals containing edge discontinuities
Year
DOI
Venue
1988
10.1109/ICASSP.1988.196711
New York, NY
Keywords
DocType
ISSN
filtering and prediction theory,filters,coefficient censoring,edge retention,filter span,median filter,optimal censored filters,order statistic filters,rank-order filters,robustness,smoothing performance,trimmed mean filters,parameter estimation,statistics,order statistic,adaptive filters,operating systems
Conference
1520-6149
Citations 
PageRank 
References 
2
3.35
0
Authors
2
Name
Order
Citations
PageRank
Naaman, L.123.35
Alan C. Bovik23341274.64