DocumentCode :
749865
Title :
Optimal weighted median filtering under structural constraints
Author :
Yang, Ruikang ; Yin, Lin ; Gabbouj, Moncef ; Astola, Jaakko ; Neuvo, Yrjo
Author_Institution :
Nokia Res. Center, Tampere, Finland
Volume :
43
Issue :
3
fYear :
1995
fDate :
3/1/1995 12:00:00 AM
Firstpage :
591
Lastpage :
604
Abstract :
A new expression for the output moments of weighted median filtered data is derived. The noise attenuation capability of a weighted median filter can now be assessed using the L-vector and M-vector parameters in the new expression. The second major contribution of the paper is the development of a new optimality theory for weighted median filters. This theory is based on the new expression for the output moments, and combines the noise attenuation and some structural constraints on the filter´s behavior. In certain special cases, the optimal weighted median filter can be obtained by merely solving a set of linear inequalities. This leads in some cases to closed form solutions for optimal weighted median filters. Some applications of the theory developed in this paper, in 1-D signal processing and image processing are discussed. Throughout the analysis, some striking similarities are pointed out between linear FIR filters and weighted median filters
Keywords :
circuit optimisation; filtering theory; image processing; median filters; noise; signal processing; 1-D signal processing; closed form solutions; image processing; linear FIR filters; linear inequalities; noise attenuation; optimal weighted median filtering; optimality theory; output moments; structural constraints; vector parameters; weighted median filtered data; Attenuation; Closed-form solution; Constraint theory; Filtering theory; Finite impulse response filter; Neural networks; Noise reduction; Nonlinear filters; Signal processing; Signal processing algorithms;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.370615
Filename :
370615
Link To Document :
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