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http://dx.doi.org/10.6109/jkiice.2014.18.3.727

Image Restoration for Edge Preserving in Mixed Noise Environment  

Long, Xu (Department of Control and Instrumentation Engineering, Pukyong National University)
Kim, Nam-Ho (Department of Control and Instrumentation Engineering, Pukyong National University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.18, no.3, 2014 , pp. 727-734 More about this Journal
Abstract
Digital processing technologies are being studied in various areas of image compression, recognition and recovery. However, image deterioration still occurs due to the noises in the process of image acquisition, storage and transmission. Generally in the typical noises which are included in the images, there are Gaussian noise and the mixed noise where the Gaussian noise and impulse noise are overlapped and in order to remove these noises, various researches are being executed. In order to preserve the edge and effectively remove mixed noises, image recovery filter algorithm was suggested in this study which sets and processes the adaptive weight using the median values and average values after noise judgment. Additionally, existing methods were compared through simulations and PSNR(peak signal to noise ratio) was used as a judgment standard.
Keywords
Image Processing; Mixed Noise; Adaptive Weighted; Image Restoration;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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1 Xu Long and Nam-Ho Kim, "An Improved Adaptive Median Filter for Impulse Noise Removal", Journal of KIICE, vol. 17, no. 4, pp. 989-995, Apr., 2012.
2 Zhu Lin, "A Non-local Means based Adaptive De-noising Framework for Mixed Image Noise Removalenter Weighted Median Filters and Their Applications to Image Enhancement", 2013 20th IEEE International Conference on Image Processing (ICIP), pp. 454-458, Sep., 2013.
3 Jian Zhang, Ruiqin Xiong, Chen Zhao, Siwei Ma, and Debin Zhao, "Exploiting Image Local and Non-local Consistency for Mixed Gaussian-Impulse Noise Removal", 2012 IEEE International Conference on Multimedia and Expo (ICME), pp. 592-597, July, 2012.
4 Zhou, Y.Y., Ye, Z.F., Huang, J.J, "Improved Decisionbased Detail-Preserving Variational Method for Removal of Random-Valued Impulse Noise," Published in IET Image Processing, vol. 6, no. 7, pp. 978-985, May, 2012.
5 Y. Li, L. X. Shen, D. Dai, and B. Suter, "Framelet Algorithms for De-blurring Images Corrupted by Impulse plus Gaussian Noise," IEEE Trans. on Image Process., vol. 20, no. 7, pp. 1822-1837, July, 2011.   DOI   ScienceOn
6 Jian Wu and Chen Tang, "PDE-Based Random-Valued Impulse Noise Removal Based on New Class of Controlling Functions" IEEE Trans. Image Process, vol. 20, no. 9, pp. 2428-2438, Sep., 2011.   DOI   ScienceOn
7 He Changwei, Liu Yingxia, Ren Wenjie and Wang Xin, "Wavelet De-noising based on Multistage Median Filtering", Journal of Computer Application, vol. 27, no. 9, pp. 2117-2119, Sep., 2007.
8 K. Bodduna, R. Siddavatam, "A Novel Algorithm for Detection and Removal of Random Valued Impulse Noise using Cardinal Splines", India Conference (INDICON), 2012 Annual IEEE, pp. 1003-1008, Dec., 2012.
9 S. J. Ko and Y. H. Lee, "Center Weighted Median Filters and Their Applications to Image Enhancement", IEEE Transactions, on Circuits and Systems, vol. 38, no. 9, pp. 984-993, Sep., 1991.   DOI   ScienceOn
10 Gao Yinyu and Nam-Ho Kim, " The Modified Nonlinear Filter to Remove Impulse Noise", Journal of KIICE, vol. 15, no. 4, pp. 973-979, Apr., 2011.
11 D.. S. Lalush, "Binary Encoding of Multiplexed Images in Mixed Noise", IEEE Trans. on Medical Imaging, vol. 27, no. 9, pp. 1323-1332, Sep., 2008. and Communication Sciences Conference, pp. 463-466, 2008.   DOI   ScienceOn
12 R. C. Gonzalez and R.E. woods, Eds., Digiral Image Processing, Prentice Hall, 2007.
13 Wang, Z., Zhang, D., "Progressive Switching Median Filter for the Removal of Impulse Noise from Highly Corrupted Images", IEEE Trans. Circuits Syst. II, Analog Digit. Signal Process, vol. 46, no. 1, pp. 78-80, Jan., 1999.   DOI   ScienceOn
14 Gao Yinyu and Nam-Ho Kim, "A Study on Image Restoration for Removing Mixed noise while Considering Edge Information", International Journal of KIICE, vol. 15, no. 10, pp. 2239-2246, Oct., 2011.
15 D. Baljozovic, B. Kovacevic, A. Baljozovic, "Mixed Noise Removal Filter for Multi-Channel Images based on Half-Space Deepest Location", Image Processing, IET, vol. 7, no. 4, pp. 310-323, June, 2013.   DOI   ScienceOn
16 Kuk-Seung Kim, Kyung-Hyo Lee, Nam-Ho Kim, "A Study on Robust Median Filter in Impulse Noise Environment", Proceedings of the Korean Institute of Information and Communication Sciences Conference, pp. 463-466, 2008.
17 Smail Akkoul, Roger Ledee, Remy Leconge, and Rachid Harbaao, "A New Adaptive Switching Median Filter", IEEE Signal Processing Letters, vol. 17, no. 6, pp. 587-590, June, 2010.   DOI   ScienceOn
18 Hwang, H., Haddad R. A., "'Adaptive Median Filters: New Algorithms and Results", IEEE Trans. Image Process, vol. 4, no. 4, pp. 499-502, Apr., 1995.   DOI   ScienceOn
19 T. Chen and H. R. Wu, "Adaptive Impulse Detection using Center Weighted Median Filters". IEEE Signal Processing Letters, vol 8, no. 1, pp. 1-3, Jan., 2001.   DOI   ScienceOn
20 A. Fabijanska, D. Sankowski, "Noise Adaptive Switching Median-based Filter for Impulse Noise Removal from Extremely Corrupted Images", Image Processing, IET, vol. 7, no. 5, pp. 472-480, Aug., 2011.
21 RChan R.H., Hu C., Nikolova M.,"An Iterative Procedure for Removing Random-Valued Impulse Noise", IEEE Signal Processing Letters, vol. 11, no. 12, pp. 921-924, Dec., 2004   DOI   ScienceOn