TY - JOUR
T1 - RM-filtering procedures in image and video processing
AU - Ponomaryov, Volodymyr I.
AU - Gallegos-Funes, F. J.
AU - Ponomaryova, Lyubov O.
PY - 2003
Y1 - 2003
N2 - In this paper we present the robust Cascaded RM-filter to remove the mixture of impulsive and multiplicative noise from corrupted images. The designed filter uses combined R- and M-estimators called RM-estimators. The capability of the impulsive noise removal in the image processing applications by using of the RM-KNN (MM-KNN, WM-KNN, ABSTM-KNN or MoodM-KNNN) are presented. The presented Cascaded RM-filter is the consequential connection of two filters. The first filter uses one of the proposed filters to provide impulsive noise rejection and detail preservation. The second one uses an M-filter to provide multiplicative noise suppression. We investigated various types of influence functions used in the M-estimator of designed filter. Extensive simulation results in reference images have demonstrated that the proposed filters consistently can outperform other nonlinear filters by balancing the tradeoff between noise suppression and detail preservation. The criterions used to compare performance were the PSNR and MAE. Finally, we also present the real-time implementation of proposed filter using DSP TMS320C6701 to demonstrate that it potentially provides a real-time solution to quality TV/video transmission.
AB - In this paper we present the robust Cascaded RM-filter to remove the mixture of impulsive and multiplicative noise from corrupted images. The designed filter uses combined R- and M-estimators called RM-estimators. The capability of the impulsive noise removal in the image processing applications by using of the RM-KNN (MM-KNN, WM-KNN, ABSTM-KNN or MoodM-KNNN) are presented. The presented Cascaded RM-filter is the consequential connection of two filters. The first filter uses one of the proposed filters to provide impulsive noise rejection and detail preservation. The second one uses an M-filter to provide multiplicative noise suppression. We investigated various types of influence functions used in the M-estimator of designed filter. Extensive simulation results in reference images have demonstrated that the proposed filters consistently can outperform other nonlinear filters by balancing the tradeoff between noise suppression and detail preservation. The criterions used to compare performance were the PSNR and MAE. Finally, we also present the real-time implementation of proposed filter using DSP TMS320C6701 to demonstrate that it potentially provides a real-time solution to quality TV/video transmission.
KW - DSP
KW - Rank-M filters
KW - Real imaging
KW - Robust image processing
UR - http://www.scopus.com/inward/record.url?scp=0141719381&partnerID=8YFLogxK
U2 - 10.1117/12.503164
DO - 10.1117/12.503164
M3 - Artículo de la conferencia
AN - SCOPUS:0141719381
SN - 0277-786X
VL - 5150 III
SP - 1630
EP - 1641
JO - Proceedings of SPIE - The International Society for Optical Engineering
JF - Proceedings of SPIE - The International Society for Optical Engineering
T2 - Visual Communications and Image Processing 2003
Y2 - 8 July 2003 through 11 July 2003
ER -