Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
The Combination of Evidence in the Transferable Belief Model
IEEE Transactions on Pattern Analysis and Machine Intelligence
Artificial Intelligence
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
Evidence Theory and Its Applications
Evidence Theory and Its Applications
Fast detection and impulsive noise removal in color images
Real-Time Imaging - Special issue on multi-dimensional image processing
Fuzzy random impulse noise reduction method
Fuzzy Sets and Systems
Multi-scale data fusion using Dempster-Shafer evidence theory
Integrated Computer-Aided Engineering
Generalized selection weighted vector filters
EURASIP Journal on Applied Signal Processing
Progressive decision-based mean type filter for image noise suppression
Computer Standards & Interfaces
A signal detection system based on Dempster-Shafer theory andcomparison to fuzzy detection
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Tri-state median filter for image denoising
IEEE Transactions on Image Processing
A universal noise removal algorithm with an impulse detector
IEEE Transactions on Image Processing
Hi-index | 12.05 |
A novel decision-based fuzzy averaging (DFA) filter consisting of a D-S (Dempster-Shafer) noise detector and a two-pass noise filtering mechanism is presented in this paper. The proposed filter can effectively deal with impulsive noise, and a mix of Gaussian and impulsive noise. Bodies of evidence are extracted, and the basic belief assignment is developed using the simple support function, which avoids the counter-intuitive problem of Dempster's combination rule. The combination belief value is the decision rule for the D-S noise detector. A fuzzy averaging method, where the weights are constructed using a predefined fuzzy set, is developed to achieve noise cancellation. A simple second-pass filter is employed to improve the final filtering performance. Experimental results confirm the effectiveness of the new DFA filter both in suppressing impulsive noise as well as a mix Gaussian and impulsive noise and in improving perceived image quality.