On the computational complexity of multivariate median filters
Signal Processing
Color image processing and applications
Color image processing and applications
Handbook of Image and Video Processing
Handbook of Image and Video Processing
Fast adaptive similarity based impulsive noise reduction filter
Real-Time Imaging - Special issue on spectral imaging
Selection weighted vector directional filters
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Real-Time Color Image Processing Using Order Statistics Filters
Journal of Mathematical Imaging and Vision
ABST M-Type K-Nearest Neighbor (ABSTM-KNN) for Image Denoising
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Vector Median M-Type L Filter to Process Multichannel Images
CIARP '08 Proceedings of the 13th Iberoamerican congress on Pattern Recognition: Progress in Pattern Recognition, Image Analysis and Applications
Directional processing of color images: theory and experimental results
IEEE Transactions on Image Processing
Color image processing using adaptive multichannel filters
IEEE Transactions on Image Processing
Color local complexity estimation based steganographic (CLCES) method
Expert Systems with Applications: An International Journal
Pattern Recognition Letters
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In this paper, we introduce the Vector Rank M-type L (VRML)-filter to remove impulsive noise from color images and video sequences. The proposed filter uses the Median M-type (MM) and Ansari-Bradley-Siegel-Tukey M-type (AM) estimators into L-filter to provide robustness to proposed filtering scheme. We also introduce the use of impulsive noise detectors to improve the properties of noise suppression and detail preservation in the proposed filtering scheme in the case of low and high densities of impulsive noise. Simulation results indicate that the proposed filter consistently outperforms other color image filters by balancing the trade-off between noise suppression, detail preservation, and color retention.