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Super Resolution Reconstruction in Mixed Noise Environment

by A.geetha Devi, T.madhu, K.lal Kishore
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 12
Year of Publication: 2015
Authors: A.geetha Devi, T.madhu, K.lal Kishore
10.5120/21594-4689

A.geetha Devi, T.madhu, K.lal Kishore . Super Resolution Reconstruction in Mixed Noise Environment. International Journal of Computer Applications. 121, 12 ( July 2015), 33-41. DOI=10.5120/21594-4689

@article{ 10.5120/21594-4689,
author = { A.geetha Devi, T.madhu, K.lal Kishore },
title = { Super Resolution Reconstruction in Mixed Noise Environment },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 12 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 33-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number12/21594-4689/ },
doi = { 10.5120/21594-4689 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:08:15.569404+05:30
%A A.geetha Devi
%A T.madhu
%A K.lal Kishore
%T Super Resolution Reconstruction in Mixed Noise Environment
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 12
%P 33-41
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

A hybrid Super Resolution (SR) algorithm is proposed to deal with the Low Resolution (LR) images degraded by Mixed (Gaussian + Impulse) noise. The algorithm adaptively estimates and removes the impulse noise from the input LR images based on edge, geometrical & size characteristics. The fuzzy based impulse noise removal algorithm is along with adaptive sharpening filter based SR using steering kernel regression are used to obtain a HR image. The experimental results confirm the efficacy of the algorithm for different types of images at various noise densities.

References
  1. Sung Cheol Park, Min Kyu Park, Moon Gi Kang, May 2003 "Super Resolution Image Reconstruction: A Technical Overview", IEEE Signal processing magazine, Vol 20. No. 3 pp: 21-36,
  2. Subhasis Chaudhuri," 2001,Super Resolution Imaging", Kluwer Academic publishers,.
  3. Tania Stathaki, "Image Fusion: Algorithms and Applications" First edition ,Academic Press is an imprint of Elsevier,
  4. Ajay Kumar Nain, Surbhi Singhania, Shailender Gupta and Bharat Bhushan, 2014, " A Comparative Study of Mixed Noise Removal Techniques", International Journal of Signal Processing, Image Processing and Pattern Recognition Vol. 7, No. 1, pp. 405-414
  5. A. Geetha Devi, T. Madhu, K. Lal Kishore, 2015, "Detection, Tracking and Identification of Moving Objects in a Video using Super Resolution - A Novel Approach", International Journal of Applied Engineering Research, ISSN 0973-4562 Volume 10, Number 3, pp. 5471-5487
  6. H. Ur and D. Gross, Mar. 1992. , "Improved resolution from sub-pixel shifted pictures,"CVGIP: Graphical Models and Image Processing, vol. 54, pp. 181-186,
  7. RC. Gonzalez, RE. Woods, 2002. "Digital Image Processing",2nd ed. , Prentice Hall,
  8. Linwei Yue, Huanfeng Shen, Qiangqiang Yuan, Liangpei Zhang, 2014, "A locally adaptive L1_L2 norm for multi-frame super-resolution of images with mixed noise and outliers", Signal Processing Vol. 105, pp:156–174.
  9. Zhengya Xu, Hong Ren Wu, Bin Qiu, and Xinghuo Yu August 2009"Geometric Features-Based Filtering for Suppression of Impulse Noise in Color Images" IEEE transactions on image processing, Vol. 18, No. 8.
  10. Lowe,D. G. , July 2004, "Distinctive Image Features from Scale-Invariant Keypoint", International Journal of Computer Vision,. Vol. 59(3), PP:207–232,
  11. Arun K. S. , Sarath K. S. , October 2010, "An Automatic Feature Based Registration Algorithm For Medical Images", International Conference on Advances in Recent Technologies in Communication and Computing. , PP:174-177.
  12. David G. Lowe, September 1999, "Object recognition from local scale-invariant features," International Conference on Computer Vision, Corfu, Greece, pp. 1150-1157.
  13. Haidawati Nasir, Vladimir Stankovic and Stephen Marshall, 2012, "Singular value decomposition based fusion for super-resolution image reconstruction", Signal Processing: Image Communication 27, pp:180–191.
  14. R. Keys, Dec. 1981 "Cubic convolution interpolation for digital image processing,"IEEE Trans. Acoust. , Speech, Signal Process. , vol. ASSP-29, no. 6,pp. 1153–1160.
  15. H. Takeda, S. Farsiu, and P. Milanfar, February 2007, "Kernel regression for image processing and reconstruction", IEEE Transactions on Image Processing, 16(2), pp:349–366
  16. Y. Deng, C. Kenney, M. S. Moore and B. S. Manjunath, "Peer group filtering and perceptual color image quantization", vol. 4, July 1999, pp. 21-24
  17. R. H. Chan, C. Ho, and M. Nikolova, Oct. 2005, "Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization," IEEE Trans. Image Process. , vol. 14, no. 10, pp. 1479–1485.
  18. Y. Shen and K. E. Barner, May-June, 2004, "Fuzzy Vector Median-Based Surface Smoothing", IEEE transactions on visualization and computer graphics, vol. 10, no. 3,
  19. J. Astola, P. Haavisto and Y. Neuvo, April, 1990 "Vector Median Filters", Proceedings of IEEE, vol. 78, no. 4.
  20. E. Abreu, M. Lightstone, S. K. Mitra, K. Arakawa, 1996,A new Efficient approach for the Removal of Impulse Noise from Highly Corrupted Images, IEEE Trans. on Image Processing, Vol. 5, No. 6, pp. 1012-1025.
  21. Vivek Bannore, 2009 "Iterative-Interpolation Super-Resolution Image Reconstruction - A Computationally Efficient Technique", Springer-Verlag Berlin Heidelberg.
  22. A. K. Jain, 1989, "Fundamentals of Digital Image Processing", Engelwood Cliff, N. J. : Prentice Hall.
  23. B. Zhang and J. P. Allebach, May 2008, "Adaptive bilateral filter for sharpness enhancement and noise removal", IEEE Trans. on Image Processing, 17(5):664–678
  24. Syed Ali, "Adaptive Filtering Techniques", IEEE Press, Wiley Inter Science, A John Wiley & Sons, Inc. ,Publication
Index Terms

Computer Science
Information Sciences

Keywords

Geometric features Steering kernel regression SIFT based registration Interpolation.