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Hybrid Adaptive Image Restoration Method with Pixel Block Estimation and Histogram Equalization

by Sukhwinder Singh, Amit Grover
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 148 - Number 6
Year of Publication: 2016
Authors: Sukhwinder Singh, Amit Grover
10.5120/ijca2016911144

Sukhwinder Singh, Amit Grover . Hybrid Adaptive Image Restoration Method with Pixel Block Estimation and Histogram Equalization. International Journal of Computer Applications. 148, 6 ( Aug 2016), 12-15. DOI=10.5120/ijca2016911144

@article{ 10.5120/ijca2016911144,
author = { Sukhwinder Singh, Amit Grover },
title = { Hybrid Adaptive Image Restoration Method with Pixel Block Estimation and Histogram Equalization },
journal = { International Journal of Computer Applications },
issue_date = { Aug 2016 },
volume = { 148 },
number = { 6 },
month = { Aug },
year = { 2016 },
issn = { 0975-8887 },
pages = { 12-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume148/number6/25760-2016911144/ },
doi = { 10.5120/ijca2016911144 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:52:35.976698+05:30
%A Sukhwinder Singh
%A Amit Grover
%T Hybrid Adaptive Image Restoration Method with Pixel Block Estimation and Histogram Equalization
%J International Journal of Computer Applications
%@ 0975-8887
%V 148
%N 6
%P 12-15
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The process of recovering image from corrupted state is called restoration. In this paper, the combination of the neighbor based reference model and non-reference image matrix enhancement is proposed for the enhancement of the results. In this paper the restoration with image missing pixel recovery and recreation is done and non-reference restoration enhancement method is used to recover the pixel expansion problem. Then image is more enhanced by using Histogram. The experimental results have been executed over the grayscale standard images of the Lena and Barbara. The results have shown that the proposed model outperforms the existing models when evaluated on the basis of peak signal to noise ratio and mean squared error.

References
  1. A.Gotchev, J. Vesma, T. Saramaki and K. Egiazarian," Digital image re sampling by modified B-spline functions,"IEEE Nordic Signal Processing symposium, pp. 259-262, June 2000.
  2. A. M. Darwish, M. S. Bedair and S.I. Shaheen, “Adaptive resampling algorithm for image enhancement”, IEEE Proc. Vis. Image Signal Process, vol. 144, pp 207-212 No. 4, August 1997.
  3. Andera Giachetti and Nicola Asuni, “Real-Time artifact free Image up scaling”, IEEE Transactions on Image Processing, vol. 20 No. 10, October 2011.
  4. B. S. Morse and D. Schwartzwald,"Image magnification using level-set reconstruction", Proc. IEEE Int. Cof. Computer Vision Pattern Recognition, vol.3, pp. 333-340, 2001.
  5. Buades, Antoni, Bartomeu Coll, and Jean-Michel Morel. "Nonlocal image and movie denoising." International journal of computer vision 76.2, pp. 123-139, 2008
  6. C. B. Atkins, C. A. Bouman and J. P. Allebach, “Optimal image scaling using pixel classification”, Proc. IEEE Int. Conf. Image Processing, vol. 3, pp. 864-867, 2001.
  7. Concus, P., Golub, G. H., & O'Leary,' D. P. A generalized conjugate gradient method for the numerical: Solution of elliptic partial differential equations: Computer Science Department, School of Humanities and Sciences. : Stanford University, 1976
  8. Gonzalez, Rafael C. "RE woods, Digital Image Processing." Addison–Wesely Publishing Company (1992).
  9. H. chen and G. E. Ford,"An FIR enhancement filter Design method based on properties of Human Vision", Proc. IEEE Int. Conf. Image Processing, vol.3, PP.581-585, November 1994.
  10. Mihalache, Constantina Raluca, and Mitica Craus. "Neural network and fuzzy membership functions based edge detection for digital images." System Theory, Control and Computing (ICSTCC), 16th International Conference on. IEEE, PP 1-6, 2012.
  11. Xue Li, GaoShesheng, Wang Jianchao, “Research on Robust Unscented Regularized Particle Filtering,” IEEE, pp. 790-793, 2010.
  12. Lai, Yang-Chih, et al. "PSO-based estimation for Gaussian blur in blind image deconvolution problem." Fuzzy Systems (FUZZ), 2011 IEEE International Conference on. IEEE, PP 1143-1148, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Image enhancement contrast enhancement noise elimination contrast adjustment.

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