Vector rank m-type K-nearest neighbor filters for multichannel image processing
Francisco Javier Gallegos-Funes, Volodymyr I. Ponomaryov, Alberto Rosales · 2005
We present the Vector Rank M-type K-Nearest Neighbor (VRMKNN) filter to remove impulsive noise from color images. This filter utilizes multichannel image processing by using the vector approach and the Rank M-Type K-Nearest Neighbor (RMK) algorithm. The implementation of the that the proposed filter potentially could provide a real-time solution to quality of imagelvideo transmision. Simulation results indicate that the proposed filter consistently outperforms other coior image filters by balancing the tradeoff between noise suppression and detail preservation. I (1) id e,, =- In this paper, we introduce the Vector Rank M-Type K- Nearest Neighbor (VRMKNN) filter. This filter utilizes multichannel image processing by using the vector approach, and the Rank M-Type K-Nearest Neighbor (RMKNN) algorithm. The VRMKNN filter provides detail preservation by use the K algorithm, and the combined RM-estimators to obtain sufficient impulsive noise suppression. The RM-estimators utilize the redescending M- estimators with different influence functions combined with the R- (median, or Wilcoxon) estimators to provide noise suppression. The real-time implementation of a filter was realized on the Texas Instruments DSP TMS320C6711 to demonstrate that the proposed filter potentially could provide a real-time solution to quality imagelvideo transmission. Simulation results have demonstrated that the proposed filter consistently outperforms other color image filters by balancing the tradeoff between noise suppression and detail preservation.