Title :
GMLOS: a new robust nonlinear filter for image processing applications
Author :
Rabiee, Hamid R. ; Kashyap, R.L.
Author_Institution :
Dept. of Electr. Eng., Purdue Univ., West Lafayette, IN, USA
Abstract :
The restoration and enhancement of degraded images are of fundamental importance in image processing applications. The authors introduce a new robust nonlinear filter (single and multistage) based on generalized maximum likelihood reasoning and order statistics (GMLOS). This new filter is not only capable of attenuating the noise and presenting the derails, but also has the ability to sharpen the edges. In addition, it does not require any type of threshold or weighting factor and is computationally efficient. Some of the experimental results on real images are also provided
Keywords :
filtering and prediction theory; image processing; image reconstruction; maximum likelihood estimation; statistics; GMLOS; computational efficiency; degraded images; edges sharpening; enhancement; generalized maximum likelihood reasoning; image processing applications; noise; order statistics; restoration; robust nonlinear filter; single multistage filter; Additive noise; Degradation; Digital filters; Digital images; Image processing; Image restoration; Noise robustness; Nonlinear filters; Smoothing methods; Statistics;
Conference_Titel :
Signals, Systems and Computers, 1993. 1993 Conference Record of The Twenty-Seventh Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-4120-7
DOI :
10.1109/ACSSC.1993.342445
