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Reseach Article

A DWT-SWT based Image Super Resolution with Multi Surface Fitting

by Gogireddy Sneha, T.ramakrishnaiah
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 103 - Number 15
Year of Publication: 2014
Authors: Gogireddy Sneha, T.ramakrishnaiah
10.5120/18149-9399

Gogireddy Sneha, T.ramakrishnaiah . A DWT-SWT based Image Super Resolution with Multi Surface Fitting. International Journal of Computer Applications. 103, 15 ( October 2014), 9-13. DOI=10.5120/18149-9399

@article{ 10.5120/18149-9399,
author = { Gogireddy Sneha, T.ramakrishnaiah },
title = { A DWT-SWT based Image Super Resolution with Multi Surface Fitting },
journal = { International Journal of Computer Applications },
issue_date = { October 2014 },
volume = { 103 },
number = { 15 },
month = { October },
year = { 2014 },
issn = { 0975-8887 },
pages = { 9-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume103/number15/18149-9399/ },
doi = { 10.5120/18149-9399 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:34:37.720649+05:30
%A Gogireddy Sneha
%A T.ramakrishnaiah
%T A DWT-SWT based Image Super Resolution with Multi Surface Fitting
%J International Journal of Computer Applications
%@ 0975-8887
%V 103
%N 15
%P 9-13
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper, an image super-resolution technique is proposed which is based on interpolation of high frequency sub-band images obtained by Discrete Wavelet Transform on input image. In those sub-bands edges are enhanced by introducing an intermediate stage by using Stationary Wavelet Transform. The wavelet transform is applied in order to decompose image into different sub-bands. In those sub-bands, the high frequency sub-bands are interpolated and then these estimated high frequency sub-bands are modified by using high frequency sub-bands obtained through SWT. These all sub-bands are fused to generate a new high resolution by using inverse Wavelet transform techniques. The proposed results depict the conventional and state of art image resolution enhancement techniques.

References
  1. H. Demirel, G. Anbarjafari, and S. Izadpanahi, "Improved motionbased localized super resolution technique using discrete wavelet transform for low resolution video enhancement," in Proc. 17th Eur. Signal Process. Conf. , Glasgow, Scotland, Aug. 2009, pp. 1097–1101. .
  2. Y. Piao, I. Shin, and H. W. Park, "Image resolution enhancement using inter-subband correlation in wavelet domain," in Proc. Int. Conf. Image Process. , 2007, vol. 1, pp. I-445–448.
  3. H. Demirel and G. Anbarjafari, "Satellite image resolution enhancement using complex wavelet transform," IEEE Geoscience and Remote Sensing Letter, vol. 7, no. 1, pp. 123–126, Jan. 2010.
  4. C. B. Atkins, C. A. Bouman, and J. P. Allebach, "Optimal image scaling using pixel classification," in Proc. Int. Conf. Image Process. , Oct. 7–10, 2001, vol. 3, pp. 864–867.
  5. J. E. Fowler, "The redundant discrete wavelet transform and additive noise,"Mississippi State ERC, Mississippi State University, Tech. Rep. MSSU-COE-ERC-04-04, Mar. 2004.
  6. S. Mann and R. W. Picard, "Video orbits of the projective group: A simple approach to featureless Processing, vol. 6, no. 9, pp. 1281–1295, September 1997.
  7. S. Lertrattanapanich and N. K. Bose, "Latest Results on High-Resolution Reconstruction From Video Sequences, Technical Report of IEICE," The Institution of Electronic, Information and Communication Engineers, Japan, DSP99-140, 1999.
  8. N. K. Bose and K. J. Boo, "High-resolution image reconstruction with multisensors," International Journal Imaging Systems and Technology, vol. 9, pp. 294–304, 1998.
  9. M. K. Ng, J. Koo, and N. K. Bose, "Constrained total least-squares computations for high-resolution image reconstruction with multisensors," International Journal Imaging Systems and Technology, vol. 12, pp. 35–42, 2002.
  10. N. Nguyen and P. Milanfar, "A wavelet-based interpolation-restoration method for superresolution (wavelet superresolution)," Circuits Systems Signal Process, vol. 19, no. 4, pp. 321–338, 2000.
  11. N. K. Bose and S. Lertrattanapanich, "Advances in wavelet superresolution," in SAMPTA 2001: Proceedings of International Conference on Sampling Theory and Application, May 13–17, 2001, pp. 5–12.
  12. L. Poletto and P. Nicolosi, "Enhancing the spatial resolution of a two-dimensional discrete array detector," Opt. Eng. , vol. 38, no. 10, pp. 1748–1757, October 1999.
Index Terms

Computer Science
Information Sciences

Keywords

Image super resolution Discrete and stationary wavelet transform.