Distance-Based Mean Filter for Image Denoising

In this paper, we propose distance-based mean filter (DBMF) to remove the salt and pepper noise. Although DBMF also uses the adaptive conditions like AMF, it uses distance-based mean instead of median. The distance-based mean focuses on similarity of pixels based on distance. It also skips noisy pixels from evaluating new gray value. Hence, DBMF works more effectively than AMF. In the experiments, we test on 20 images of the MATLAB library with various noise levels. We also compare denoising results of DBMF with other similar denoising methods based on the peak signal-to-noise ratio and the structure similarity metrics. The results showed that DBMF can effectively remove noise with various noise levels and outperforms other methods.

[1]  Jinsong Wu,et al.  Partial differential equation diffusion in complex domain , 2016, 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[2]  Ronald R. Coifman,et al.  In Wavelets and Statistics , 1995 .

[3]  Song Guo,et al.  Information and Communications Technologies for Sustainable Development Goals: State-of-the-Art, Needs and Perspectives , 2018, IEEE Communications Surveys & Tutorials.

[4]  Tong-Li He,et al.  A new method of removing salt-and-pepper noise basing on grey system model in images , 2010, 2010 IEEE International Conference on Intelligent Computing and Intelligent Systems.

[5]  Li Bai,et al.  Implementation of high‐order variational models made easy for image processing , 2016 .

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

[7]  I. Johnstone,et al.  Adapting to unknown sparsity by controlling the false discovery rate , 2005, math/0505374.

[8]  Uğur Erkan,et al.  A new method based on pixel density in salt and pepper noise removal , 2018, Turkish J. Electr. Eng. Comput. Sci..

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

[10]  Le Minh Hieu,et al.  An Iterative Mean Filter for Image Denoising , 2019, IEEE Access.

[11]  Dang N. H. Thanh,et al.  An Improved BPDF Filter for High Density Salt and Pepper Denoising , 2019, 2019 IEEE-RIVF International Conference on Computing and Communication Technologies (RIVF).

[12]  Mohammad Shorif Uddin,et al.  Gaussian noise reduction in digital images using a modified fuzzy filter , 2014, 2014 17th International Conference on Computer and Information Technology (ICCIT).

[13]  Mizuki Tomita,et al.  Evaluating multiple classifier system for the reduction of salt-and-pepper noise in the classification of very-high-resolution satellite images , 2018, International Journal of Remote Sensing.

[14]  I. Johnstone,et al.  Needles and straw in haystacks: Empirical Bayes estimates of possibly sparse sequences , 2004, math/0410088.

[15]  Guna Seetharaman,et al.  Multiscale Tikhonov-Total Variation Image Restoration Using Spatially Varying Edge Coherence Exponent , 2015, IEEE Transactions on Image Processing.

[16]  Ashwin Thakur,et al.  AN IMPROVED APPROACH FOR REMOVAL OF HIGH DENSITY SALT AND PEPPER NOISE THROUGH MODIFIED DECISION BASED UNSYMMETRIC TRIMMED MEDIAN FILTER , 2015 .

[17]  Dang N. H. Thanh,et al.  A Review on CT and X-Ray Images Denoising Methods , 2019, Informatica.

[18]  Vikrant Bhateja,et al.  Performance Improvement of Decision Median Filter for Suppression of Salt and Pepper Noise , 2014, SIRS.

[19]  Yong Cheng,et al.  Modified directional weighted filter for removal of salt & pepper noise , 2014, Pattern Recognit. Lett..

[20]  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.

[21]  S Shaik Majeeth,et al.  Gaussian Noise Removal in an Image using Fast Guided Filter and its Method Noise Thresholding in Medical Healthcare Application , 2019, Journal of Medical Systems.

[22]  V. B. Surya Prasath,et al.  On Selecting the Appropriate Scale in Image Selective Smoothing by Nonlinear Diffusion , 2018, 2018 IEEE Seventh International Conference on Communications and Electronics (ICCE).

[23]  Chunwei Tian,et al.  Image denoising using deep CNN with batch renormalization , 2020, Neural Networks.

[24]  Nishchal K. Verma,et al.  Adaptive Type-2 Fuzzy Approach for Filtering Salt and Pepper Noise in Grayscale Images , 2018, IEEE Transactions on Fuzzy Systems.

[25]  Paul Rodríguez,et al.  Spatially adaptive Total Variation image denoising under salt and pepper noise , 2011, 2011 19th European Signal Processing Conference.

[26]  Wichian Premchaiswadi,et al.  A scheme for salt and pepper noise reduction and its application for OCR systems , 2010 .

[27]  Jorge Herbert de Lira,et al.  Two-Dimensional Signal and Image Processing , 1989 .

[28]  Surya Prasath,et al.  Structure tensor adaptive total variation for image restoration , 2019, TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES.

[29]  V. B. Surya Prasath,et al.  Total Variation L1 Fidelity Salt-and-Pepper Denoising with Adaptive Regularization Parameter , 2018, 2018 5th NAFOSTED Conference on Information and Computer Science (NICS).