Adaptive, Noise-Exclusive and Assessment-Based Fuzzy Switching Median Filter For High Intensity Impulse Noise

The article proposes an adaptive, noise-exclusive and assessment-based fuzzy switching median filter for high intensity impulse noise. The filter adaptively changes the size of sliding window in accordance with noise intensity and noise-exclusive operation is performed only on noise-free pixels. These steps thus preserve the image details effectively. Judicious assessment of the previously restored pixels is made in order to use them in replacing the noisy pixels and further improve the efficiency of filter. With these possibilities, fuzzy switching median filter-based approach is also incorporated for improving the performance. Experimental results justified the efficacy of the proposed fuzzy-based filtering method qualitatively and quantitatively for twelve different highly corrupted noisy images, and showed significant improvement to existing algorithms.

[1]  Mingyue Ding,et al.  Decision-based non-local means filter for removing impulse noise from digital images , 2013, Signal Process..

[2]  T. Nodes,et al.  Median filters: Some modifications and their properties , 1982 .

[3]  Sung-Jea Ko,et al.  Center weighted median filters and their applications to image enhancement , 1991 .

[4]  Saroj K. Meher.  Recursive and noise-exclusive fuzzy switching median filter for impulse noise reduction , 2014, Eng. Appl. Artif. Intell..

[5]  Saroj K. Meher,et al.  An improved recursive and adaptive median filter for high density impulse noise , 2014 .

[6]  Liangliang Zhu,et al.  A Local Similarity Pattern for Removal of Random Valued Impulse Noise , 2014, J. Multim..

[7]  Gang Xiong,et al.  ADWA: A filtering paradigm for signal's noise removal and feature preservation , 2013, Signal Process..

[8]  Nor Ashidi Mat Isa,et al.  Noise Adaptive Fuzzy Switching Median Filter for Salt-and-Pepper Noise Reduction , 2010, IEEE Signal Processing Letters.

[9]  Kai-Kuang Ma,et al.  A switching median filter with boundary discriminative noise detection for extremely corrupted images , 2006, IEEE Trans. Image Process..

[10]  Yi Zhou,et al.  Impulse noise removal by a nonmonotone adaptive gradient method , 2010, Signal Process..

[11]  Veerakumar Thangaraj,et al.  Removal of High Density Salt and Pepper Noise Through Modified Decision Based Unsymmetric Trimmed Median Filter , 2011, IEEE Signal Processing Letters.

[12]  Haidi Ibrahim,et al.  Salt-and-pepper noise detection and reduction using fuzzy switching median filter , 2008, IEEE Transactions on Consumer Electronics.

[13]  David Ebenezer,et al.  A New Fast and Efficient Decision-Based Algorithm for Removal of High-Density Impulse Noises , 2007, IEEE Signal Processing Letters.

[14]  Raymond H. Chan,et al.  Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization , 2005, IEEE Transactions on Image Processing.

[15]  Vikas Gupta,et al.  Random-valued impulse noise removal using adaptive dual threshold median filter , 2015, J. Vis. Commun. Image Represent..

[16]  Samuel Morillas,et al.  Fuzzy Peer Groups for Reducing Mixed Gaussian-Impulse Noise From Color Images , 2009, IEEE Transactions on Image Processing.

[17]  Qian Zhang,et al.  A new salt and pepper noise removal filtering algorithm , 2012, World Automation Congress 2012.

[18]  Wen-June Wang,et al.  Fuzzy reasoning-based directional median filter design , 2009, Signal Process..

[19]  Dehua Li,et al.  Modified switching median filter for impulse noise removal , 2010, Signal Process..

[20]  Ping Guo,et al.  Removal of random-valued impulse noise by local statistics , 2014, Multimedia Tools and Applications.

[21]  Impulse Noise Removal From Digital Images by a Detail-Preserving Filter Based on Type-2 Fuzzy Logic , 2008 .

[23]  Eero P. Simoncelli,et al.  Image quality assessment: from error visibility to structural similarity , 2004, IEEE Transactions on Image Processing.

[24]  Xun Gong,et al.  Using Sorted Switching Median Filter to remove high-density impulse noises , 2013, J. Vis. Commun. Image Represent..