Median filter based on fuzzy rules and its application to image restoration
Fuzzy Sets and Systems - Special issue on fuzzy signal processing
Communications of the ACM
Digital Image Processing
Fuzzy random impulse noise reduction method
Fuzzy Sets and Systems
Knowledge and Information Systems
Knowledge and Information Systems
Spatially adaptive image restoration using fuzzy punctual kriging
Journal of Computer Science and Technology
Modified Histogram Based Fuzzy Filter
MIRAGE '09 Proceedings of the 4th International Conference on Computer Vision/Computer Graphics CollaborationTechniques
A new multiobjective clustering technique based on the concepts of stability and symmetry
Knowledge and Information Systems
Histogram-based fuzzy filter for image restoration
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Genetic-based fuzzy image filter and its application to image processing
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Noise adaptive soft-switching median filter
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
A fuzzy impulse noise detection and reduction method
IEEE Transactions on Image Processing
Quantum and impulse noise filtering from breast mammogram images
Computer Methods and Programs in Biomedicine
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In this paper, we propose an image filtering technique based on fuzzy logic control to remove impulse noise for low as well as highly corrupted images. The proposed method is based on noise detection, noise removal and edge preservation modules. The main advantage of the proposed technique over the other filtering techniques is its superior noise removal as well as detail preserving capability. Based on the criteria of peak-signal-to-noise-ratio (PSNR), mean square error (MSE), structural similarity index measure (SSIM) and subjective evaluation measure we have found experimentally that the proposed method provides much better performance than the state-of-the-art filters. To analyze the detail preservation capability of the proposed filter sensitivity analysis is performed by changing the detail preservation module to see its effects on the details (texture and edge information) of resultant image. This sensitivity analysis proves experimentally that significant image details have been preserved by the proposed method.