A new impulse detection and filtering method for removal of wide range impulse noises

Authors:
Shuenn-Shyang Wang;Cheng-Hao Wu
Affiliations:
Department of Electrical Engineering, Tatung University, 40 Chungshan N. Road, 3rd Sec., Taipei, Taiwan, ROC;Department of Electrical Engineering, Tatung University, 40 Chungshan N. Road, 3rd Sec., Taipei, Taiwan, ROC
Venue:
Pattern Recognition
Year:
2009

Citing 3
Cited 9

A New Efficient Impulse Detection Algorithm for the Removal of Impulse Noise

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Noise adaptive soft-switching median filter

IEEE Transactions on Image Processing
Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization

IEEE Transactions on Image Processing

Restoration of images corrupted by Gaussian and uniform impulsive noise

Pattern Recognition
Modified switching median filter for impulse noise removal

Signal Processing
Two-step fuzzy logic-based method for impulse noise detection in colour images

Pattern Recognition Letters
Restoration of images corrupted by mixed Gaussian-impulse noise via l1-l0 minimization

Pattern Recognition
Restoration of embedded image from corrupted stego image

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
Fast communication: Decision-based non-local means filter for removing impulse noise from digital images

Signal Processing
Dictionary learning based impulse noise removal via L1-L1 minimization

Signal Processing
Salt and pepper noise filtering with fuzzy-cellular automata

Computers and Electrical Engineering

Quantified Score

Hi-index	0.01

Visualization

Abstract

A new impulse detection and filtering algorithm is proposed for restoration of images that are highly corrupted by impulse noise. It is based on the minimum absolute value of four convolutions obtained by one-dimensional Laplacian operators. The proposed algorithm can effectively remove the impulse noise with a wide range of noise density and produce better results in terms of the qualitative and quantitative measures of the images even at noise density as high as 90%. Extensive simulations show that the proposed algorithm provides better performance than many of the existing switching median filters in terms of noise suppression and detail preservation.