Title :
Nonlinear image filtering in a mixture of Gaussian and heavy-tailed noise
Author :
Hamza, A. Ben ; Krim, Hamid
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fDate :
6/23/1905 12:00:00 AM
Abstract :
Inspired by robust estimation, nonlinear denoising methods combining the mean, the median, and the LogCauchy filters are proposed. Some statistical and asymptotic properties are studied, and comparisons with other nonlinear filtering schemes are performed. Experimental results showing a much improved performance of the proposed filters in the presence of Gaussian and heavy-tailed noise are analyzed and illustrated
Keywords :
Gaussian noise; filtering theory; median filters; nonlinear estimation; nonlinear filters; statistical analysis; Gaussian noise; LogCauchy filters; asymptotic properties; heavy-tailed noise; mean filter; median filter; nonlinear denoising; nonlinear filtering; nonlinear image filtering; performance; robust estimation; statistical properties; Filtering; Filters; Gaussian distribution; Gaussian noise; Laplace equations; Noise reduction; Noise robustness; Performance analysis; Probability distribution; Wavelet coefficients;
Conference_Titel :
Statistical Signal Processing, 2001. Proceedings of the 11th IEEE Signal Processing Workshop on
Print_ISBN :
0-7803-7011-2
DOI :
10.1109/SSP.2001.955229
