The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Constrained adaptive LMS L-filters
Signal Processing
Detail-preserving median based filters in image processing
Pattern Recognition Letters
Median filter based on fuzzy rules and its application to image restoration
Fuzzy Sets and Systems - Special issue on fuzzy signal processing
Introduction to data compression
Introduction to data compression
Suppression of “salt and pepper” noise based on Youden designs
Information Sciences: an International Journal
Convergence behavior of the LMS algorithm in subband adaptive filtering
Signal Processing
LUM smoother with smooth control for noisy image sequences
EURASIP Journal on Applied Signal Processing
Evolutionary modeling and inference of gene network
Information Sciences—Informatics and Computer Science: An International Journal - Bioinformatics-selected papers from 4th CBGI & 6th JCIS Proceedings
Decision tree learning with fuzzy labels
Information Sciences—Informatics and Computer Science: An International Journal
Improved structure-adaptive anisotropic filter
Pattern Recognition Letters
Fast detection and impulsive noise removal 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
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Impulse noise removal by multi-state median filtering
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04
Cost-effective video filtering solution for real-time vision systems
EURASIP Journal on Applied Signal Processing
Generalized selection weighted vector filters
EURASIP Journal on Applied Signal Processing
LUM filters: a class of rank-order-based filters for smoothing andsharpening
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Adaptive LMS L-filters for noise suppression in images
IEEE Transactions on Image Processing
Tri-state median filter for image denoising
IEEE Transactions on Image Processing
Fingerprint enhancement by shape adaptation of scale-space operators with automatic scale selection
IEEE Transactions on Image Processing
A universal noise removal algorithm with an impulse detector
IEEE Transactions on Image Processing
Switching-based filter based on Dempster's combination rule for image processing
Information Sciences: an International Journal
Application of SVM-based filter using LMS learning algorithm for image denoising
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Information Sciences: an International Journal
Fuzzy based diffusion coefficient function in anisotropic diffusion for impulse noise removal
Proceedings of the Eighth Indian Conference on Computer Vision, Graphics and Image Processing
Joint image denoising using adaptive principal component analysis and self-similarity
Information Sciences: an International Journal
Partition-based fuzzy median filter based on adaptive resonance theory
Computer Standards & Interfaces
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In this work, a new adaptive center weighted median (ACWM) filter is proposed for improving the performance of median-based filters, preserving image details while effectively suppressing impulsive noise. The proposed filter is an adaptive CWM filter with an adjustable central weight obtained by partitioning the observation vector space. To obtain the optimal weight for each block, the efficient scalar quantization (SQ) method is used to partition the observation vector space. The center weight within each block is obtained by using a learning approach based on the least mean square (LMS) algorithm. The noise filtering procedure is progressively applied through several iterations so that the mean square error of the output can be minimized. Experimental results have demonstrated that the proposed filter outperforms many well-accepted median-based filters in terms of both noise suppression and detail preservation. The proposed new filter also provides excellent robustness at various percentages of impulsive noise.