Research Article
Super-Resolution using Interpolation and Wavelet Lifting Scheme
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 40 - Issue 13 |
| Published: February 2012 |
| Authors: Sapan Naik, Viral Borisagar |
10.5120/5038-7357
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Sapan Naik, Viral Borisagar . Super-Resolution using Interpolation and Wavelet Lifting Scheme. International Journal of Computer Applications. 40, 13 (February 2012), 7-11. DOI=10.5120/5038-7357
@article{ 10.5120/5038-7357,
author = { Sapan Naik,Viral Borisagar },
title = { Super-Resolution using Interpolation and Wavelet Lifting Scheme },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 40 },
number = { 13 },
pages = { 7-11 },
doi = { 10.5120/5038-7357 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Sapan Naik
%A Viral Borisagar
%T Super-Resolution using Interpolation and Wavelet Lifting Scheme%T
%J International Journal of Computer Applications
%V 40
%N 13
%P 7-11
%R 10.5120/5038-7357
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Due to the limitation of image capturing technique, we often get low resolution(LR) images. We can construct high resolution(HR) images from one or more LR images and this method is called Super Resolution(SR). In this paper we have proposed one lifting based super resolution algorithm which generate super resolution image from three rotated, noisy and blurred images. We have used HAAR wavelet lifting scheme and ASWDR encoding method. To remove noise and blur from original images we have applied Gaussian filter and Iterative Blind Deconvolution(IBD) algorithm.
References
- Rohit Arora, Madan lal Sharma, Nidhika Birla, “An Algorithm for Image Compression Using 2D Wavelet Transform” , International Journal of Engineering Science and Technology (IJEST) ISSN : 0975-5462 Vol. 3 No. 4 Apr 2011 pp. 2758 – 2764.
- Vinay U. Kale, Nikkoo N. Khalsa, “Performance Evaluation of Various Wavelets for Image Compression of Natural and Artificial Images” ,International Journal of Computer Science & Communication, Vol. 1, No. 1, January-June 2010, pp. 179-184.
- R.Sudhakar, Ms R Karthiga, S.Jayaraman, “Image Compression using Coding of Wavelet Coefficients – A Survey”, ICGST-GVIP Journal, Volume (5), Issue (6), June 2005, pp.25-38.
- James S. Walker, “Wavelet-based Image Compression” , Sub-chapter of CRC Press book: Transforms and Data Compression.
- Ashwini M. Deshpande, Suprava Patnaik, Comparative Study and Qualitative-Quantitative Investigations of Several Motion Deblurring Algorithms,2nd International Conference and workshop on Emerging Trends in Technology (ICWET) 2011,(IJCA),pg 27-34.
- Ping-Sing Tsai, Tinku Acharya,” Image Up-Sampling Using Discrete Wavelet Transform”, 9th JCIS 2006, 8 to 11 October 2006.
- S. C. Park, M. K. Park, and M. G. Kang, “Super-resolution image reconstruction: A technical review,” IEEE Signal Processing Mag., vol. 20, pp. 21–36, May 2003.
- Sina Jahanbin, Richard Naething, “Super-resolution Image Reconstuction Performance”, May 16, 2005
- S. Chaudhuri, Ed., Super-Resolution Imaging. Norwell, MA: Kluwer, 2001.
- S.P. Kim, N.K. Bose, and H.M. Valenzuela, “Recursive reconstruction of high resolution image from noisy undersampled multiframes,” IEEE Trans.Acoust., Speech, Signal Processing, vol. 38, pp. 1013-1027, June 1990.
- Ayers G. R., and Dainty J. C. Iterative blind deconvolution methods and its applications. Optics Letter, vol. 13, no. 7, July 1988.
- E.D. Castro, C. Morandi, “Registration of translated and rotated images using finite Fourier transform” , IEEE Transactions on Pattern Analysis and Machine Intelligence 700–703,1987.
- A.Jensen, A.la Courharbo, “ Ripples in Mathematics : The Discrete Wavelet Transform”, springer,2001.
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