DocumentCode :
3073539
Title :
A comparison of image filtering algorithms
Author :
Dravida, S. ; Woods, J.U. ; Shen, U.C.
Author_Institution :
Rensselaer Polytechnic Institute, Troy, New York, USA
Volume :
9
fYear :
1984
fDate :
30742
Firstpage :
259
Lastpage :
262
Abstract :
This paper compares four image filtering algorithms on common data sets for various signal to noise ratios and white Gaussian noise. The algorithms are the median filter, the Wallis filter, the reduced update Kalman filter, and a multiple model, decision-directed filter. This comparison produces some surprising results from both a subjective (visual error) and a mean square error (MSE) viewpoint.
Keywords :
Data engineering; Filtering algorithms; Gaussian noise; Image processing; Maximum likelihood detection; Mean square error methods; Nonlinear filters; Signal to noise ratio; Statistics; Systems engineering and theory;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech, and Signal Processing, IEEE International Conference on ICASSP '84.
Type :
conf
DOI :
10.1109/ICASSP.1984.1172540
Filename :
1172540
Link To Document :
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