Color image processing and applications
Color image processing and applications
Adaptive vector median filtering
Pattern Recognition Letters
Adaptive Color Image Filtering Based on Center-Weighted Vector Directional Filters
Multidimensional Systems and Signal Processing
Selection weighted vector directional filters
Computer Vision and Image Understanding - Special issue on color for image indexing and retrieval
Fast detection and impulsive noise removal in color images
Real-Time Imaging - Special issue on multi-dimensional image processing
A neighborhood evaluated adaptive vector filter for suppression of impulse noise in color images
Real-Time Imaging - Special issue on multi-dimensional image processing
A fast impulsive noise color image filter using fuzzy metrics
Real-Time Imaging - Special issue on multi-dimensional image processing
Sharpening vector median filters
Signal Processing
Fast detection and removal of impulsive noise using peer groups and fuzzy metrics
Journal of Visual Communication and Image Representation
Isolating impulsive noise pixels in color images by peer group techniques
Computer Vision and Image Understanding
Fuzzy peer groups for reducing mixed Gaussian-impulse noise from color images
IEEE Transactions on Image Processing
Peer group switching filter for impulse noise reduction incolor images
Pattern Recognition Letters
Adaptive edge enhancing technique of impulsive noise removal in color digital images
CCIW'11 Proceedings of the Third international conference on Computational color imaging
Rank-Ordered differences statistic based switching vector filter
ICIAR'06 Proceedings of the Third international conference on Image Analysis and Recognition - Volume Part I
IEEE Transactions on Image Processing
A universal noise removal algorithm with an impulse detector
IEEE Transactions on Image Processing
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In the paper a fast technique of impulsive noise removal in color images is described. The proposed method is assigning to pixels of the filtering window the sum of the distances to their k nearest neighbors. The difference between the trimmed sum assigned to the central pixel and to the pixel minimizing the cumulated distances is treated as a measure of pixel's distortion caused by the impulsive noise process. If the difference exceeds a global threshold value, then the central pixel of the processing window is replaced by the mean of the pixels from the window, which were found to be not corrupted, otherwise the central pixel is retained. The new filtering design is able to effectively suppress impulsive noise, while preserving fine image details. The performance comparison shows that the proposed filtering design yields significantly better denoising results than the most efficient filters developed for the impulsive noise suppression in color images.