Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

This is an Open Access publication published under CSC-OpenAccess Policy.
Image Super-Resolution using Single Image Semi Coupled Dictionary Learning
Hemant S. Goklani, Shravya S., Jignesh N. Sarvaiya
Pages - 135 - 144     |    Revised - 30-06-2016     |    Published - 31-07-2016
Volume - 10   Issue - 3    |    Publication Date - July 2016  Table of Contents
Super-resolution, Single Image Super Resolution (SISR), Single Image Semi Coupled Dictionary (SI-SCDL).
Obtaining a high resolution image from a low resolution image plays an important role in many image processing applications. In Single Image Super Resolution (SISR), the desired high resolution output image is synthesized from a single low resolution input image. In this paper, Single Image Semi Coupled Dictionary Learning (SI-SCDL) method is proposed, where the dictionaries to represent the high and low resolution images are trained from the input image itself. In the proposed method, the online training stage is employed, where the dictionaries are learnt online and it does not require any external training database. Simulation results show that the proposed SI-SCDL method performs better when compared to other mentioned methods.
CITED BY (0)  
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PdfSR
1 R. Keys, “Cubic convolution interpolation for digital image processing. Acoustics, Speech and Signal Processing”, IEEE Trans on, vol. 29(6), pp. 1153-1160, 1981.
2 X. Zhang and X. Wu. Image interpolation by adaptive 2-d autoregressive modeling and soft-decision estimation. IEEE Trans on IP, vol. 17(6), pp. 887-896, 2008.
3 X. Li and M. Orchard, “New edge directed interpolation, IEEE Trans on IP, vol.10, no. 10, pp.1521-1527, 2001.
4 S. Mallat and G. Yu, “Super-resolution with sparse mixing estimators”, IEEE Trans on IP, vol.19(11), pp. 2889-2900, 2010.
5 W. T. Freeman, T. Jones, and E. Pasztor “Example based super-resolution”, IEEE Computer Graphics and Applications, 2002.
6 J. Yang, J. Wright, T. Huang, and Y. Ma, “Image super-resolution via sparse representation”, IEEE Trans. Image Process.,vol 19(11), pp.2861-2873, 2010.
7 Daniel Glasner, Bagon Shai, Michal Irani, “Super-resolution from a single image”,12th International Conference on Computer Vision, IEEE, 2009.
8 Jianchao Yang, John Wright, Thomas Huang, and Yi Ma, “Image super-resolution as sparse representation of raw image patches”, IEEE Conference on Computer Vision and Pattern Recognition, CVPR, 2008.
9 Jianchao Yang, John Wright, Thomas Huang, and Yi Ma, “Image super-resolution via sparse representation”, IEEE Transactions on Image Processing, vol. 19, no. 11, pp. 2861-2873, 2010.
10 B. Efron, T. Hastie, I. Johnstone, and R. Tibshirani, “Least angle regression”, The Annals of statistics, vol. 32(2), pp.407-499, 2004.
11 M. Yang, L. Zhang, J. Yang, and D. Zhang, “Metaface learning for sparse representation based face recognition”, In ICIP, pp. 1601-1604. IEEE, 2010.
12 A. G.Weber, “The USC-SIPI Image Database”, tech. rep., University of Southern California, Signal and Image Processing Institute, Department of Electrical Engineering, Los Angeles, CA 90089, 2564 USA, 3740 McClintock Ave, 1997.
13 D. Martin, C. Fowlkes, D. Tal, and J. Malik, “A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics”, in Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, 2, vol.2, pp. 416-423, 2001.
14 S. Wang, L. Zhang, L. Y., and Q. Pan, Semi-coupled dictionary learning with applications in image super-resolution and photo-sketch synthesis, in International Conference on Computer Vision and Pattern Recognition (CVPR), IEEE, 2012.
15 Chang, Hong, Dit-Yan Yeung, and Yimin Xiong. "Super-resolution through neighbor embedding." In Computer Vision and Pattern Recognition, 2004. CVPR 2004. Proceedings of the 2004 IEEE Computer Society Conference on, vol. 1, pp. I-I. IEEE, 2004.
Mr. Hemant S. Goklani
SVNIT - India
Miss Shravya S.
SVNIT - India
Dr. Jignesh N. Sarvaiya
SVNIT - India