TY - JOUR
T1 - Denoising robust image filter with retention of small-size details in presence of complex noise mixture
AU - Ponomaryov, Volodymyr I.
AU - Funes, Francisco J.Gallegos
AU - Pogrebnyak, Oleksiy B.
AU - De Rivera, Luis Nino
PY - 2002
Y1 - 2002
N2 - In this paper, we present the implementation of the robust detail preserving filters with complex noise suppression for image processing applications. The designed filter is the consequential connection of two filters. The first filter uses the value of central pixel of the filtering window to provide the preservation of fine details and the redescending M-estimators combined with the median estimator to provide impulsive noise rejection. The second filter uses the output of the first filter as the pre-estimator for an adaptive calculation in the redescending M-estimator. We investigated various types of influence functions in the M-estimator those are similar to the ones used in the Sigma filter to provide multiplicative noise suppression. The optimal values of the parameters of designed filters in presence of different noise mixture are determined. Different simulation data are presented in the paper and shown the statistical efficiency of the filters.
AB - In this paper, we present the implementation of the robust detail preserving filters with complex noise suppression for image processing applications. The designed filter is the consequential connection of two filters. The first filter uses the value of central pixel of the filtering window to provide the preservation of fine details and the redescending M-estimators combined with the median estimator to provide impulsive noise rejection. The second filter uses the output of the first filter as the pre-estimator for an adaptive calculation in the redescending M-estimator. We investigated various types of influence functions in the M-estimator those are similar to the ones used in the Sigma filter to provide multiplicative noise suppression. The optimal values of the parameters of designed filters in presence of different noise mixture are determined. Different simulation data are presented in the paper and shown the statistical efficiency of the filters.
KW - Order Statistics Filters
KW - RM estimators
KW - RM-KNN filters
UR - http://www.scopus.com/inward/record.url?scp=0036028963&partnerID=8YFLogxK
U2 - 10.1117/12.453132
DO - 10.1117/12.453132
M3 - Artículo de la conferencia
AN - SCOPUS:0036028963
SN - 0277-786X
VL - 4671 II
SP - 877
EP - 887
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
T2 - Viual Communications and Image Processing 2002
Y2 - 21 January 2002 through 23 January 2002
ER -