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Wavelet based Technique for Super Resolution Image Reconstruction

International Journal of Computer Applications
© 2011 by IJCA Journal
Volume 33 - Number 7
Year of Publication: 2011
Mathew .K.
Dr. S. Shibu

Mathew .K. and Dr. S Shibu. Article: Wavelet based Technique for Super Resolution Image Reconstruction. International Journal of Computer Applications 33(7):11-17, November 2011. Full text available. BibTeX

	author = {Mathew .K. and Dr. S. Shibu},
	title = {Article: Wavelet based Technique for Super Resolution Image Reconstruction},
	journal = {International Journal of Computer Applications},
	year = {2011},
	volume = {33},
	number = {7},
	pages = {11-17},
	month = {November},
	note = {Full text available}


The super resolution means the quality of the image to the extent of the maximum capability of the technology referring it. The image capturing devices have their hardware limitations to reach to the perfection. A technique for Reconstruction of super resolution image using low resolution natural color image has been developed. The presented technique identifies local features of low resolution image and then enhances its resolution appropriately. It is noticed that the higher PSNR is observed for the developed technique than the existing methods.


  • T. Komatsu, K. Aizawa, T. Igarashi, and T. Saito, “Signal-processing based method for acquiring very high resolution image with multiple cameras and its theoretical analysis,” Proc. Inst. Elec. Eng., vol. 140, no. 1, pt. I, pp.19-25, Feb. 1993.
  • S. Borman and R.L. Stevenson, “Spatial resolution enhancement of low-resolution image sequences. A comprehensive review with directions for future research,” Lab. Image and Signal Analysis, University of Notre Dame, Tech. Report, 1998.
  • Sung Cheol Park, Min Kyu Park, and Moon Gi Kang, “Super-Resolution Image Reconstruction: A Technical Overview”, IEEE Signal Processing Magazine, May 2003; a special issue on Super Resolution Imaging. pp 21-36
  • Thomas M Lehman, Claudia and Klaus, “Survey: Interpolation Methods in Medical Image Processing”, IEEE Transaction on Medical Imaging Vol 18, No 11, Nov 1999, pp 1049-1075
  • Einar Maeland, “ On the Comparison of Interpolation Methods”, IEEE Transaction on Medical Imaging, Vol 7, No 3, Sept 1998, pp-213-217
  • Erik Meijering, “ A Chronology of Interpolation”, Proceedings of IEEE, Vol 90, no.3, March 2002, pp- 319-342
  • Rafael C. Gonzalez, Richard E. Woods,” Digital Image Processing”, Pearson Education, ISBN 81-7808-629-8, 2002.
  • A. K. Jain, “Fundamentals of Digital Image Processing” Pearson Education, ISBN 81-297-0083-2, 2003.
  • R. Y. Tsai and T. S. Huang, “Multiframe image restoration and registration,” in Advances in Computer Vision and Image Processing, vol. 1, chapter 7, pp. 317–339, JAI Press, Greenwich, Conn, USA, 1984.
  • Sina Farsiu, Dirk Robinson, Michael Elad, Peyman Milanfar, ”Advances and Challenges in Super-Resolution”, J. Imag. Syst. Technol., Wiley Periodicals, Inc. vol. 14, no. 2, pp. 47–57, Oct. 2004.
  • Patrick Vandewalle, L Sbaiz, J Vandewalle and M Vetterli, “Super Resolution from Unregistered and Totally Aliased Signals Using Subspace Methods”, IEEE Tranc on Signal Processing, vol 25, no 7, July 2007
  • Frank M. Candocia, and Jose C. Principe, “Super-Resolution of Images Based on Local Correlations” IEEE Transactions On Neural Networks, Vol. 10, No. 2, March 1999 pp 372-380
  • Olcay Kursun and Oleg Favorov, “Single frame super resolution by a Cortex based mechanism using high level visual features in natural images”, Proc. Of IEEE ICWACV 2002.
  • W. T. Freeman, T. R. Jones, and E. C. Pasztor, “Example-based super-resolution”, IEEE Computer Graphics and Applications, vol. 22, no. 2, pp. 56–65, 2002.
  • C V Jijji, and S. Choudhari, “ Single Frame Image Super Resolution Through Contourlet Learning”, “Super-Resolution-Imaging: Analysis, Algorithms, and Applications”, EURASIP Journal on Applied Signal Processing, 2006 DOI 10.1155/ASP/2006/73767,PP-1-11
  • C. V. Jiji, M. V. Joshi, and S. Chaudhuri, “Single-frame image super-resolution using learned wavelet coefficients,” International Journal of Imaging Systems and Technology, vol. 14, no. 3, pp. 105–112, 2004.
  • Mahesh Chappalli and N K Bose, “Simultaneous Noise Filtering and Super Resolution with Second Generation Wavelets”, IEEE Signal Processing letters, vol 12, n0 11, Nov 2005, pp- 772-775.
  • Zhao, Hua Han and Silong Peng, “ Wavelet Domain HMT Based Image Super resolution”, Proceeding of International Conf. PP II-953-956.
  • Choong boon, Onur Guleryuz, Toshiro and Y Suzuki, “ Sparse Super resolution reconstruction of video from mobile devices in digital TV broadcast applications PS-2006-0117”, Research Laboratories, NTT DoCoMo Inc, Japan.
  • N K Bose and S Lertrattanapanich, “Advances in Wavelet Super resolution”, The spatial and temporal signal processing center, PSU, PA, USA pp 1-8
  • N. K. Bose, Mahesh B. Chappalli, “A Second-Generation Wavelet Framework for Super-Resolution with Noise Filtering” , International Journal of IST, wiley publications, 2004, vol 4, pp-84-89
  • El-Sayed Wahed, “Image enhancement using second generation wavelet super resolution”, International Journal of Physical Sciences, Vol 2 (6), June 2007, pp 149-158
  • S.E. Khamy, Hadhaud, Dessouky, Salam, and Abd El-Samie, “A New Super resolution Reconstruction Algorithm Based on Wavelet Fusion” , 22nd National Radio Science conference NRSC 2005, Cairo, Egypt.
  • H.C. Liu, Y feng, and G Y Sun, “ Wavelet Domain Image Super Resolution Reconstruction Based on Image Pyramids and Cycle Spinning”, Journal of Physics: Conference Series 48 (2006) pp 4117-4121
  • Antonio Turiel, German Mato, Nestor parga, “Self-similarity properties of Natural Images”, Laboratory de Physique Statistics de, et aux Universities paris