A new method based on pixel density in salt and pepper noise removal

In this paper, we deliver a new method to remove salt and pepper noise, which we refer to as based on pixel density filter (BPDF). The first step of the method is to determine whether or not a pixel is noisy, and then we decide on an adaptive window size that accepts the noisy pixel as the center. The most repetitive noiseless pixel value within the window is set as the new pixel value. By using 18 test images, we give the results of peak signal-to-noise ratio (PSNR), structural similarity (SSIM), image enhancement factor (IEF), standard median filter (SMF), adaptive median filter (AMF), adaptive fuzzy filter (AFM), progressive switching median filter (PSMF), decision-based algorithm (DBA), modified decision-based unsymmetrical trimmed median filter (MDBUTMF), noise adaptive fuzzy switching median filter (NAFSM), and BPDF. The results show that BPDF produces better results than the above-mentioned methods at low and medium noise density.

[1]  Kostas D. Tsirikolias,et al.  Low level image processing and analysis using radius filters , 2016, Digit. Signal Process..

[2]  Sumit Agrawal,et al.  An Improved Decision based Asymmetric Trimmed Median Filter for Removal of High Density Salt and Pepper Noise , 2013 .

[3]  Suman Shrestha.  Image Denoising using New Adaptive Based Median Filters , 2014, ArXiv.

[4]  Pierrick Coupé,et al.  Adaptive multiresolution non-local means filter for three-dimensional magnetic resonance image denoising , 2012 .

[5]  Jian Yu,et al.  Restoration of images corrupted by mixed Gaussian-impulse noise via l1-l0 minimization , 2011, Pattern Recognit..

[6]  Hong Liu,et al.  Improved bilateral filter for suppressing mixed noise in color images , 2012, Digit. Signal Process..

[7]  N. Velmurugan Nagappan,et al.  Noise free image restoration using hybrid filter with adaptive genetic algorithm , 2016 .

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

[9]  Sharad Agarwal,et al.  A New and Efficient Method for Removal of High Density Salt and Pepper Noise Through Cascade Decision based Filtering Algorithm , 2012 .

[10]  Branko Kovacevic,et al.  Mixed noise removal filter for multi-channel images based on halfspace deepest location , 2013, IET Image Process..

[11]  K. Vasanth,et al.  Decision-based neighborhood-referred unsymmetrical trimmed variants filter for the removal of high-density salt-and-pepper noise in images and videos , 2015, Signal Image Video Process..

[12]  Gonzalo R. Arce,et al.  A general weighted median filter structure admitting negative weights , 1998, IEEE Trans. Signal Process..

[13]  Zhenjun Tang,et al.  Salt and pepper noise removal with image inpainting , 2015 .

[14]  Zhou Wang,et al.  Progressive switching median filter for the removal of impulse noise from highly corrupted images , 1999 .

[15]  Jianfen Ma,et al.  An Algorithm for Salt and Pepper Noise Removal Based on Information Entropy , 2012 .

[16]  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.

[17]  Adem Kilicman,et al.  Two new methods for removing salt - and - pepper noise from digital images , 2016 .

[18]  Arpad Gellert,et al.  Context-based prediction filtering of impulse noise images , 2016, IET Image Process..

[19]  Richard A. Haddad,et al.  Adaptive median filters: new algorithms and results , 1995, IEEE Trans. Image Process..

[20]  Bernardino Roig,et al.  Localised rank-ordered differences vector filter for suppression of high-density impulse noise in colour images , 2016, IET Image Process..

[21]  Fang Li,et al.  A New Adaptive Weighted Mean Filter for Removing Salt-and-Pepper Noise , 2014, IEEE Signal Processing Letters.

[22]  A. Vijendran,et al.  Fast and Efficient Method for Image Denoising , 2013 .

[23]  T. Palabas,et al.  Adaptive fuzzy filter combined with median filter for reducing intensive salt and pepper noise in gray level images , 2012, 2012 International Symposium on Innovations in Intelligent Systems and Applications.

[24]  A DECISION BASED UNSYMMETRICAL TRIMMED MIDPOINT ALGORITHM FOR THE REMOVAL OF HIGH DENSITY SALT AND PEPPER NOISE , 2012 .

[25]  Moncef Gabbouj,et al.  Weighted median filters: a tutorial , 1996 .

[26]  Zongze Wu,et al.  An enhancement method for X-ray image via fuzzy noise removal and homomorphic filtering , 2016, Neurocomputing.

[27]  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.

[28]  Xinjun Zhu,et al.  An efficient method for salt-and-pepper noise removal based on shearlet transform and noise detection , 2015 .

[29]  Gonzalo R. Arce,et al.  Recursive weighted median filters admitting negative weights and their optimization , 2000, IEEE Trans. Signal Process..

[30]  J. Astola,et al.  Fundamentals of Nonlinear Digital Filtering , 1997 .

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

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

[33]  Kaifu Wang,et al.  A switching median–mean filter for removal of high-density impulse noise from digital images , 2015 .

[34]  S. D. Dvoenko,et al.  A method of total variation to remove the mixed Poisson-Gaussian noise , 2016, Pattern Recognition and Image Analysis.