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Wavelet Transform based Fusion Technique for Image Restoration

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Authors:
Kalpana Wagadre, Madhu Singh
10.5120/ijca2016912208

Kalpana Wagadre and Madhu Singh. Wavelet Transform based Fusion Technique for Image Restoration. International Journal of Computer Applications 153(12):18-20, November 2016. BibTeX

@article{10.5120/ijca2016912208,
	author = {Kalpana Wagadre and Madhu Singh},
	title = {Wavelet Transform based Fusion Technique for Image Restoration},
	journal = {International Journal of Computer Applications},
	issue_date = {November 2016},
	volume = {153},
	number = {12},
	month = {Nov},
	year = {2016},
	issn = {0975-8887},
	pages = {18-20},
	numpages = {3},
	url = {http://www.ijcaonline.org/archives/volume153/number12/26542-2016912208},
	doi = {10.5120/ijca2016912208},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

there is lots of image processing algorithms to improve image quality .Image restoration is a field of image processing which deals with restoring an image that has been degraded by some degradation phenomenon. Degradation may occur due to motion blur, Gaussian blur, noise or camera mismatch. The aim of image restoration is to reconstruct or estimate an uncorrupted image by using the degraded version of the same image. [2] In this paper we described a method to remove the motion blur present in the image taken from any cameras by which motion blurred and noisy image is first restored using Wiener and Lucy Richardson method then applied wavelet based fusion Technique is applied for restoration. The performance of the every stage is tabulated for the parameters like SNR and RMSE of the restored images. It is observed that image fusion technique provides better results as compared to previous techniques. Performance of all the methods has been compared on the basis of performance parameters MSE and PSNR.

References

  1. R. C. Gonzalez, R. E. Woods, S. L. Eddins, “Digital image processing using MATLAB” Pearson, 3rd Edition 2005
  2. A. U. Gupta, “Image Restoration Using Wavelet Based Image Fusion”, Vol. 3, 2 Feb 2011.
  3. A. K. Jain, “Fundamental of digital image processing”, PHI 2005.
  4. Y. Xia, and M. S. Kamel “Novel cooperative neural fusion algorithms for image restoration, image fusion”, Feb 2007.
  5. M.Tico,M.Vehvilainen,NokiaResearchCentreFinland, This e-mail address is being protected from spambots. You need JavaScript enabled to view it , “Estimation of motion blurs PSF from differently exposed Image frames.”
  6. A. Levin, “Blind motion deblurring using image statistics”, school of computer science and Engineering, The Hebrew University, MIT CSAIL, This e-mail address is being protected from spambots. You need JavaScript enabled to view it , Jerusalem.
  7. J. Portilla, V. Strela, M. J. Wainwright and E. P. Simoncelli, “Image Denoising Using Scale Mixtures of Gaussians in the Wavelet Domain”, IEEE transactions on image processing, Vol. 12, No.11, Nov 2003.
  8. D. L. Hall and J. Llinas, “An introduction to multisensor data fusion” Processings of IEEE, Vol. 85, No. 1, Jan 1997.
  9. Deepak Kumar Sahu, M.P. Parsai, “Different image fusion techniques –a critical review”, Vol. 2, Issue. 5, Sep.-Oct. 2012, Jabalpur MP, India
  10. Y. Kurmi and V. Chaurasia, “An image fusion approach based on adaptive fuzzy logic model with local level processing,” Int. Jour. of Comp. Appl., Aug. 2015, vol. 124, no.1, pp. 39-42.
  11. D. Sharma, Y. Kurmi, and V. Chaurasia, “Formation of super- resolution image: a review,” Int. Jour. of Emerging Tech. and Adv. Engg., Apr. 2014, vol. 4, no. 4, pp. 218-221.
  12. Y. Kurmi and V. Chaurasia, “Performance of haze removal filter for hazy and noisy images,” Int. Jour. of Sci. Engg. and Tech., Apr. 2014, vol. 3 no. 4, pp. 437-439.
  13. S. Tiwari, K. Chauhan, and Y. Kurmi “Shadow detection and compensation in aerial images using MATLAB,” Int. Jour. of Comp. Appl., June 2015, vol. 119, no.20, pp. 5-9.
  14. S. Sharma, S. Sharma and R. Mehra, “Image restoration using modified Lucy Richardson algorithm in the presence of Gaussian and motion blur” Volume 3, pp. 1063-1070, Number 8 (2013).
  15. Amit S. Ufade, B.K. Khadse, S. R. Sur Aikar, “Restoration of blur image using wavelet based image fusion”, Vol.-2, no. 2, Dec, 2012.

Keywords

Image restoration, Image fusion, Wavelet, MSE, PSNR, Wiener, Lucy Richardson