A Variational Approach to Remove Outliers and Impulse Noise
Journal of Mathematical Imaging and Vision
Image Deblurring in the Presence of Impulsive Noise
International Journal of Computer Vision
Impulse noise removal by a global-local noise detector and adaptive median filter
Signal Processing - Special section: Advances in signal processing-assisted cross-layer designs
Impulsive noise suppression from images by using Anfis interpolant and lillietest
EURASIP Journal on Applied Signal Processing
Minimization of a Detail-Preserving Regularization Functional for Impulse Noise Removal
Journal of Mathematical Imaging and Vision
Progressive decision-based mean type filter for image noise suppression
Computer Standards & Interfaces
Image restoration based on Laplacian preprocessed long-range correlation
Multidimensional Systems and Signal Processing
Minimum-Maximum Exclusive Interpolation Filter for Image Denoising
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Efficient impulse noise reduction via local directional gradients and fuzzy logic
Fuzzy Sets and Systems
Automatic classification of defects in an industrial environment
Proceedings of the 2009 conference on New Directions in Neural Networks: 18th Italian Workshop on Neural Networks: WIRN 2008
Noisy image restoration based on boundary resetting BDND and median filtering with smallest window
WSEAS Transactions on Signal Processing
An intelligent image agent based on soft-computing techniques for color image processing
Expert Systems with Applications: An International Journal
ACIVS'07 Proceedings of the 9th international conference on Advanced concepts for intelligent vision systems
Switching bilateral filter with a texture/noise detector for universal noise removal
IEEE Transactions on Image Processing
Impulse noise filtering using robust pixel-wise S-estimate of variance
EURASIP Journal on Advances in Signal Processing - Special issue on robust processing of nonstationary signals
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Variational approach for restoring random-valued impulse noise
NAA'04 Proceedings of the Third international conference on Numerical Analysis and its Applications
Evolutionary tree-structured filter for impulse noise removal
ACIVS'06 Proceedings of the 8th international conference on Advanced Concepts For Intelligent Vision Systems
A novel histogram based fuzzy impulse noise restoration method for colour images
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Impulse noise detection based on robust statistics and genetic programming
ACIVS'05 Proceedings of the 7th international conference on Advanced Concepts for Intelligent Vision Systems
Efficient distortion reduction of mixed noise filters by neuro-fuzzy processing
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Using a neuro-fuzzy network for impulsive noise suppression from highly distorted images of WEB-TVs
AWIC'05 Proceedings of the Third international conference on Advances in Web Intelligence
Image deblurring in the presence of salt-and-pepper noise
Scale-Space'05 Proceedings of the 5th international conference on Scale Space and PDE Methods in Computer Vision
Information Sciences: an International Journal
Using Sorted Switching Median Filter to remove high-density impulse noises
Journal of Visual Communication and Image Representation
Partition-based fuzzy median filter based on adaptive resonance theory
Computer Standards & Interfaces
Salt and pepper noise filtering with fuzzy-cellular automata
Computers and Electrical Engineering
Hi-index | 0.02 |
We propose a decision-based, signal-adaptive median filtering algorithm for removal of impulse noise. Our algorithm achieves accurate noise detection and high SNR measures without smearing the fine details and edges in the image. The notion of homogeneity level is defined for pixel values based on their global and local statistical properties. The cooccurrence matrix technique is used to represent the correlations between a pixel and its neighbors, and to derive the upper and lower bound of the homogeneity level. Noise detection is performed at two stages: noise candidates are first selected using the homogeneity level, and then a refining process follows to eliminate false detections. The noise detection scheme does not use a quantitative decision measure, but uses qualitative structural information, and it is not subject to burdensome computations for optimization of the threshold values. Empirical results indicate that our scheme performs significantly better than other median filters, in terms of noise suppression and detail preservation.