International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 6, No. 9, 8 Aug. 2014
Cover page and Table of Contents: PDF (size: 1375KB)
A State-of-the-art Review on Wavelet Based Image Resolution Enhancement Techniques: Performance Evaluation Criteria and Issues
Full Text (PDF, 1375KB), PP.35-46
Views: 0 Downloads: 0
Author(s)
Index Terms
Image resolution, wavelet transform, fidelity criteria, PSNR, RMSE, enhancement factor, running time
Abstract
Image resolution enhancement in wavelet domain has been one of the most active research areas in image processing. Many methods and techniques, based on wavelet transformation have been proposed in last couple of years. In this paper, we present a review on the state-of-the-art techniques for wavelet based image resolution enhancement. We summarize them with enhancement ability in peak signal to noise ratio (PSNR) and give comments on their performance. In addition, through our review, we have found some essential criteria and issues related to performance assessment of different resolution enhancement techniques. Our experimental results have proved the significance of these issues. Future directions for image resolution enhancement research are stated at the end.
Cite This Paper
Samiul Azam, Fatema Tuz Zohra, Md Monirul Islam,"A State-of-the-art Review on Wavelet Based Image Resolution Enhancement Techniques: Performance Evaluation Criteria and Issues", IJIGSP, vol.6, no.9, pp.35-46, 2014. DOI: 10.5815/ijigsp.2014.09.05
Reference
[1]Yavariabdi, C. Samir, A. Bartoli, “3D Medical Image Enhancement based on Wavelet Transforms,” Proc. of the Medical image understanding and analysis conf, London, UK, Jul. 2011, pp. 172-176.
[2]S. Izadpanahi, C. Ozcinar, G. Anbarjafari, and H. Demirel, “Resolution Enhancement of Video Sequences by using Discrete Wavelet Transform and Illumination Compensation,” Turk Journal of Elec. Eng. & Comp. Sci., Vol. 03, Feb. 2011, pp. 123-131.
[3]H. Demirel and G. Anbarjafari, “Satellite Image Resolution Enhancement Using CWT,” IEEE Geo-science and Remote Sensing Letters, Vol. 07, No. 01, Jan. 2010, pp. 123–126.
[4]R. C. Gonzalez and R. E. Woods, Digital image processing: 3rd edition, Englewood Cliffs, NJ: Prentice-Hall, 2008.
[5]A. S. Glassner, K. Turkowski, and S. Gabriel, “Filters for Common Re-sampling Tasks,” Graphics Gems, New York: Academic, 1990, pp. 147–165.
[6]M. Irani and S. Peleg, “Improving Resolution by Image Registration,” CVGIP: Graph. Models Image Process, Vol. 53, No. 3, May.1991, pp. 231–239.
[7]X. Li and M.T. Orchard, “New Edge-directed Interpolation,” IEEE Trans. Image Proc., Vol. 10, No.10, Oct. 2001, pp. 1521-1527.
[8]Y. Dong and J. Ma, “Wavelet-Based Image Texture Classification Using Local Energy Histograms,” IEEE Signal Processing Letters, Vol. 18, No. 04, Apr. 2011, pp. 247-250.
[9]H. Demirel, C. Ozcinar, and G. Anbarjafari, “Satellite Image Contrast Enhancement Using Discrete Wavelet Transform and Singular Value Decomposition,” IEEE Geo-science And Remote Sensing Letters, Vol. 07, No. 02, Apr. 2010, pp. 333-337.
[10]B. Li, R. Yang and H. Jiang, “Remote-Sensing Image Compression Using Two-Dimensional Oriented Wavelet Transform,” IEEE Geo-science And Remote Sensing Letters, Vol. 49, No. 01, Jan. 2011, pp. 236-240.
[11]K. Kinebuchi, D. D. Muresan and T.W. Parks, “Image Interpolation using Wavelet-Based Hidden Markov Trees,” Proc. ICASSP ‘01, Vol. 03, May. 2001, pp. 07-11.
[12]S. Zhao, H. Han and S. Peng, “Wavelet Domain HMT-Based Image Superresolution,” IEEE International Conference on Image Proc.(ICIP), Vol.0 2, Sep. 2003, pp. 933-936.
[13]D.H. Woo, I.K. Eom and Y.S. Kim, “Image Interpolation based on Inter-scale Dependency in Wavelet Domain,” Proc. International conference of image processing (ICIP), Vol. 03, Oct. 2004, pp. 1687-1690.
[14]A. Temizel, “Image Resolution Enhancement using Wavelet Domain Hidden Markov Tree and Coefficient Sign Estimation,” Proc. International conference of image processing (ICIP), Vol. 05, 2007, pp. V-381–V-384.
[15]A. Temizel and T. Vlachos, “Wavelet Domain Image Resolution Enhancement Using Cycle Spinning,” IEE Electronics Letters, Vol. 41, No. 03, Feb. 2005, pp. 119-121.
[16]T. Celik and T. Tjahjadi, “Image Resolution Enhancement Using Dual-tree Complex Wavelet Transform,” IEEE Geo-science and Remote Sensing Letters, Vol. 7, No. 03, Dec. 2009, pp. 554 – 557.
[17]T. Celik and H. Kusetogullari, “Self-Sampled Image Resolution Enhancement Using Dual-Tree Complex wavelet Transform,” 17th European Signal Processing Conference, Aug. 2009, pp-2017-2021.
[18]A. Temizel and T. Vlachos, “Wavelet Domain Image Resolution Enhancement using Cycle Spinning and Edge Modeling,” 13th Europian signal processing conference, Sep. 2005, pp. 203-205.
[19]S. Azam, F. T. Zohra, and M. M. Islam, “Remote Sensing Image resolution Enlargement Algorithm based on Wavelet Transformation,” IJIGSP, MECS Publisher, Vol. 06, No. 03, May-2014, pp. 19-26.
[20]M. Z. Iqbal, A. Ghafoor and A. M. Siddiqui, “Satellite Image Resolution Enhancement Using Dual-Tree Complex Wavelet Transform and Nonlocal Means,” IEEE Trans. on Geo-science and Remote Sensing Letters, Vol. 10, No. 03, Jul. 2012, pp. 441-455.
[21]H. Demirel and G. Anbarjafari, “Image Super Resolution based on Interpolation of Wavelet Domain High Frequency Subbands and the Spatial Domain Input Image,” ETRI Journal, Vol. 32, No. 03, Jun. 2010, pp. 390–394.
[22]H. Demirel and G. Anbarjafari, “DWT based Satellite Image Resolution Enhancement,” IEEE transaction on Geo-science and Remote Sensing, Vol. 49, No. 06, Jun. 2011, pp. 1997–2004.
[23]H. Demirel and G. Anbarjafari, “Image Resolution Enhancement by Using Discrete and Stationary Wavelet Decomposition,” IEEE Trans. Image Processing, Vol. 20, No. 5, May. 2011, pp. 1458-1460.
[24]“Satellite Imaging Corporation,” internet: http: //www.satimagingcorp.com/gallery.html, [Oct. 07, 2013].
[25]“Hidden Markov Model,” internet: http://en.wikipedia.org/wiki/Hidden_Markov_model, [Nov. 10, 2013].
[26]Z. Wang and A. C. Bovik, “A Universal Image Quality Index,” IEEE Signal Processing Letters, Vol. 09, No.0 3, Mar. 2002. pp. 81-84.