Impulse noise removal utilizing second-order difference analysis
Signal Processing
Efficient impulse noise reduction via local directional gradients and fuzzy logic
Fuzzy Sets and Systems
Noisy image restoration based on boundary resetting BDND and median filtering with smallest window
WSEAS Transactions on Signal Processing
Fuzzy peer groups for reducing mixed Gaussian-impulse noise from color images
IEEE Transactions on Image Processing
Geometric features-based filtering for suppression of impulse noise in color images
IEEE Transactions on Image Processing
Some improvements for image filtering using peer group techniques
Image and Vision Computing
A low-cost VLSI implementation for efficient removal of impulse noise
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Switching bilateral filter with a texture/noise detector for universal noise removal
IEEE Transactions on Image Processing
EURASIP Journal on Advances in Signal Processing
WSEAS Transactions on Signal Processing
Fuzzy multipass filter for impulse noise removal in digital images
SITE'12 Proceedings of the 11th international conference on Telecommunications and Informatics, Proceedings of the 11th international conference on Signal Processing
Quantum and impulse noise filtering from breast mammogram images
Computer Methods and Programs in Biomedicine
Intelligent noise detection and filtering using neuro-fuzzy system
Multimedia Tools and Applications
Fast and efficient median filter for removing 1-99% levels of salt-and-pepper noise in images
Engineering Applications of Artificial Intelligence
Direction based adaptive weighted switching median filter for removing high density impulse noise
Computers and Electrical Engineering
Using Sorted Switching Median Filter to remove high-density impulse noises
Journal of Visual Communication and Image Representation
An effective 2-stage method for removing impulse noise in images
Journal of Visual Communication and Image Representation
Modified directional weighted filter for removal of salt & pepper noise
Pattern Recognition Letters
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A novel switching median filter incorporating with a powerful impulse noise detection method, called the boundary discriminative noise detection (BDND), is proposed in this paper for effectively denoising extremely corrupted images. To determine whether the current pixel is corrupted, the proposed BDND algorithm first classifies the pixels of a localized window, centering on the current pixel, into three groups-lower intensity impulse noise, uncorrupted pixels, and higher intensity impulse noise. The center pixel will then be considered as "uncorrupted," provided that it belongs to the "uncorrupted" pixel group, or "corrupted." For that, two boundaries that discriminate these three groups require to be accurately determined for yielding a very high noise detection accuracy-in our case, achieving zero miss-detection rate while maintaining a fairly low false-alarm rate, even up to 70% noise corruption. Four noise models are considered for performance evaluation. Extensive simulation results conducted on both monochrome and color images under a wide range (from 10% to 90%) of noise corruption clearly show that our proposed switching median filter substantially outperforms all existing median-based filters, in terms of suppressing impulse noise while preserving image details, and yet, the proposed BDND is algorithmically simple, suitable for real-time implementation and application.