Comparative Study of Major Image Enhancement Algorithms



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Submitted Jun 14, 2017
Published Jul 13, 2017
10.24018/ejeng.2017.2.7.389

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Image restoration is a process of reconstruction or recovery of an image that has been corrupted or degraded by any degradation phenomenon. Image restoration techniques are inclined towards modeling the degradation and applying the inverse process in order to recover the original image. The critical goal of restoration techniques is to improve the quality of an image in some predefined manner. This present paper is a comparative study of image enhancement techniques used for improving the quality of a given image and evaluate it against the quality of a given image and evaluate it against SNR, PSNR, MSE, and SSIM as metrics.

Keywords: Degradation Enhancement Techniques Image Noise

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  1. M. Bhowmik, D. Ghoshal S. Bhowmik, An Improved Method For The Enhancement of Under Ocean Image, IEEE ICCSP 2015 conference, 978-1- 4799-8081-9/15/, IEEE, pp1739-1742,2015
     Google Scholar
  2. Digital Image Processing book by S Jayaraman, S Esakkirajan, T Veerakumar, Fourth Reprint, Tata McGraw Hill, 2011.
     Google Scholar
  3. John Y Chiang and Ying-Ching Chen, “Underwater image enhancement by wavelength compensation and dehazing,” Image Processing, IEEE Transactions on, Vol. 21, no. 4, pp. 1756–1769, 2012.
     Google Scholar
  4. Raimondo Schettini and Silvia Corchs, "Underwater Image Processing State of the Art of Restoration and Image Enhancement Methods in EURASIP Journal on Advances in Signal Processing." Volume 2010.
     Google Scholar
  5. N. H. Sweilam,, A. M. Nagy,T. H. Farag,A. S. Abo-Elyazed, Comparative Studies for Different Image Restoration Methods, Mathematical Sciences Letters An International Journal, Math. Sci. Lett. 4, No. 2, 123-130, 2015, http://dx.doi.org/10.12785/msl/040205
     Google Scholar
  6. V. Radhika and G. Padmavathi, “Performance of Various Order Statistics Filters in Impulse and Mixed Noise Removal for RS Images”, SIPIJ, Vol,1, No.2, December 2010.
     Google Scholar
  7. Gonzalez, RC, Woods, RE &Eddins, , "Digital Image processing using MATLAB", Pearson Prentice Hall, SL 2004.
     Google Scholar