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Image Super Resolution In View of Sparse Representation

Keerthi P N1 , Shruthi M K2

Section:Research Paper, Product Type: Conference Paper
Volume-04 , Issue-03 , Page no. 97-100, May-2016

Online published on Jun 07, 2016

Copyright © Keerthi P N, Shruthi M K . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: Keerthi P N, Shruthi M K, “Image Super Resolution In View of Sparse Representation,” International Journal of Computer Sciences and Engineering, Vol.04, Issue.03, pp.97-100, 2016.

MLA Style Citation: Keerthi P N, Shruthi M K "Image Super Resolution In View of Sparse Representation." International Journal of Computer Sciences and Engineering 04.03 (2016): 97-100.

APA Style Citation: Keerthi P N, Shruthi M K, (2016). Image Super Resolution In View of Sparse Representation. International Journal of Computer Sciences and Engineering, 04(03), 97-100.

BibTex Style Citation:
@article{N_2016,
author = {Keerthi P N, Shruthi M K},
title = {Image Super Resolution In View of Sparse Representation},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {5 2016},
volume = {04},
Issue = {03},
month = {5},
year = {2016},
issn = {2347-2693},
pages = {97-100},
url = {https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=72},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_spl_paper_view.php?paper_id=72
TI - Image Super Resolution In View of Sparse Representation
T2 - International Journal of Computer Sciences and Engineering
AU - Keerthi P N, Shruthi M K
PY - 2016
DA - 2016/06/07
PB - IJCSE, Indore, INDIA
SP - 97-100
IS - 03
VL - 04
SN - 2347-2693
ER -

           

Abstract

Sparse representation has attracted it interests in the field of image resolution. On small images with certain constraints the sparsity based methods enforce sparse coding. For the observed low resolution images it has certain limitations on small scale and different scales for image sparse representation. In this paper a joint super resolution framework has been proposed to improve sparsity based image performances. The algorithm proposed here optimizes the problem for high resolution image recovery. Both the ridge regression and the gradient histogram is incorporated to solve the problem.

Key-Words / Index Term

super resolution, ridge regression, sparse representation, gradient histogram.

References

[1] X. Zhang, M. Tang, and R. Tong, “Robust super resolution of compressed video,” Vis. Comput., vol. 28, no. 12, pp. 1167–1180, 2012. I
[2] R. Y. Tsai and T. S. Huang, “Multiple frame image restoration and registration,” in Advances in Computer Vision and Image Processing, vol. 1. Greenwich, CT, USA: JAI Press, 1984
[3] Divesh N. Agrawal and Deepak Kapgate, "Face Recognition Using PCA Technique", International Journal of Computer Sciences and Engineering, Volume-02, Issue-10, Page No (59-61), Oct -2014, E-ISSN: 2347-2693
[4] M. Irani and S. Peleg, “Improving resolution by image registration,”CVGIP, Graph. Models Image Process., vol. 53, no. 3, pp. 231–239,1991.
[5] R. C. Hardie, K. J. Barnard, and E. E. Armstrong, “Joint MAP registration and high-resolution image estimation using a sequence of undersampled images,” IEEE Trans. Image Process., vol. 6, no. 12, pp. 1621–1633, Dec. 1997.
[6] S. Farsiu, M. Elad, and P. Milanfar, “Video-to-video dynamic superresolution for grayscale and color sequences,” EURASIP J. Appl. SignalProcess., vol.2006, pp. 1-15, Feb. 2006, Art. ID 061859.
[7] A. Marquina and S. J. Osher, “Image super-resolution by TV-regularization and Bregman iteration,” J. Sci. Comput., vol. 37, no. 3, pp. 367-382,2008