Brightness and Resolution Enhancement of Satellite Images using SVD and DWT
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International Journal of Engineering Trends and Technology (IJETT) |  |
| © 2013 by IJETT Journal | ||
| Volume-4 Issue-4 |
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| Year of Publication : 2013 | ||
| Authors : Ammu Anna Mathew , S. Kamatchi |
Citation
Ammu Anna Mathew , S. Kamatchi. "Brightness and Resolution Enhancement of Satellite Images using SVD and DWT". International Journal of Engineering Trends and Technology (IJETT). V4(4):712-718 Apr 2013. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group
Abstract
A new satellite image resolution and brightness enhancement technique based on the discrete wavelet transform (DWT) and singu lar value decomposition (SVD) has been proposed. Satellite images are used in many applications such as geosciences studies, astronomy, and geographical information systems. One of the most important quality factors in images comes from its resolution. The technique decomposes the input image into the four frequency sub - bands by using DWT and estimates the singular value matrix of the low – low sub band image, and, then, it reconstructs the enhanced image by applying inverse DWT. The technique also estimates the singular value matrix of the low – low sub band of histogram equalized image and normalize both singular value matrices to obtain brightness enhanced image. The technique is compared with conventional image equalization techniques such as standard gener al histogram equalization and local histogram equalization, as well as state - of - the - art techniques such as brightness preserving dynamic histogram equalization and singular value equalization. The experimental results show the superiority of the proposed m ethod over conventional and state - of - the - art technique.
References
[1] Demirel, G. Anbarjafari, and S. Izadpanahi, ?Improved motion - based localized super resolution technique using discrete wavelet transform for low resolution video enhancement,? in Proc. 17th EUSIPCO, Edinburgh, U.K., Aug. 2009, pp. 1097 – 1101.
[2] T. Celik, C. Direkoglu, H. Ozkaramanli, H. Demirel, and M. Uyguroglu, ?Region - based super - resolution aided facial feature extraction from low resolution v ideo sequences,? in Proc. IEEE ICASSP, Philadelphia, PA, Mar. 2005, vol. II, pp. 789 – 792.
[3] H. Demirel and G. Anbarjafari, ?Satellite image resolution enhancement using complex wavelet transform,? IEEE Geosci. Remote Sens. Lett., Jan. 2010, vol. 7, no. 1,pp. 123 – 126.
[4] L. Yi - bo, X. Hong, and Z. Sen - yue, ?The wrinkle generation method for facial reconstruction based on extraction of partition wrinkle line features and fractal interpolation,? in Proc. 4th ICIG, Aug. 22 – 24, 2007, pp. 933 – 937.
[5] C. B. Atkins, C. A. Bouman, and J. P. Allebach, ?Optimal image scaling using pixel classification,? in Proc. ICIP, Oct. 7 – 10, 2001, vol. 3, pp. 864 – 867 .
[6] Y. Rener, J. Wei, and C. Ken, ?Down sample - based multiple description coding and post - processing of decoding,? in Proc. 27t h CCC, Jul. 16 – 18, 2008, pp. 253 – 256
[7] Y. Piao, L. Shin, and H. W. Park, ?Image resolution enhancement using inter - sub band correlation in wavelet domain,? in Proc. IEEE ICIP, 2007, vol. 1, pp. I - 445 – I - 448.
[8] Mahesh M and Venkata Srinu. M,?Low - Resolution satel lite image enhancement using DT - CWT & SVD ? in International Journal of Advanced Research in Electronics and Communication Engineering (IJARECE) , October 2012 , Volume 1, Issue 4, pp. 40 - 45
[9] Hasanul Kabir , and Abdullah Al - Wadud , and Oksam Chae , ?Brightn ess Preserving Image Contrast Enhancement Using Weighted Mixture of Global and Local Transformation Functions ? in The International Arab Journal of Information Technology, October 2010 , Vol. 7, No. 4, pp. 403 - 410
[10] Battula.R.V.S. Narayana and K. Nirmala, ?Image Resolution Enhancement by Using Stationary and Discrete Wavelet Decomposition ? in International Journal of Modern Engineering Research (IJMER) , Sep. - Oct. 2012, Vol. 2, Issue. 5, pp - 3553 - 3555.
[11] K.Narasimhan, V.Elamaran, Saurav Kumar, Kundan Sharma a nd Pogaku Raghavendra Abhishek,? Comparison of Satellite Image Enhancement Techniques in Wavelet Domain? in Research Journal of Applied Sciences, Engineering and Technology,2012, pp.1 - 5.
[12] Dr. Muna F. Al - Samaraie and Dr. Nedhal Abdul Majied Al Saiyd,? Col ored Satellites Image Enhancement Using Wavelet and Threshold Decomposition ? in International Journal of Computer Science Issues (IJCSI), September 2011,Vol. 8, Issue 5, No 3, pp. 33 - 41
[13] R. Thriveni and Dr. Ramashri Tirumala, ?A Qualitative Approach for Resolution Enhancement of Satellite Images using 2 - DWT? in International Journal of Electronics and Communication Engineering. ISSN 0974 - 2166 Volume 5, Number 2 (2012), pp. 159 - 164
[14] Sushma Lalwani and Uzma Ansari, ?A New Approach for Increase Resolution of satellite Image? in International Journal of Emerging Technology and Advanced Engineering ,ISSN 2250 - 2459, May 2012, Volume 2, Issue 5, pp. 315 - 317.
[15] Petcharat Pattanasethanon and Boonwat Attachoo, ?Linear Filtering for Optimized Approach in Satellite Imag e Enhancement ?in Journal of Computer Science 6 (10):IS SN 1549 - 3636,2010, pp.1130 - 1136.
[16] S. Sulochana and R. Vidhya, ?Image Contrast Enhancement using Atrous Wavelet Transform and Singular Value Decomposition (SVD)? in International Journal of Computer Appl ications (0975 – 8887) September 2012, Volume 54 – No.12, pp. - 14
[17] Sulochana S and Vidhya R, ?Satellite Image Contrast Enhancement using Multiwavelets and Singular Value Decomposition (SVD)? in International Journal of Computer Applications (0975 – 8887) Dec ember 2011, Volume 35 – No.7, pp.1 - 5
[18] Hasan Demirel and Gholamreza Anbarjafari ?Discrete Wavelet Transform - Based Satellite Image Resolution Enhancement ,? in Proc. IEEE Transactions on Geoscience and Remote Sensing, Vol 49, No.6, June 2011
Keywords
Bicubic interpolation, discrete wavelet transform (DWT), mean square error (MSE), peak signal to noise ratio (PSNR), satellite resolution enhancement, satellite brightness enhancement, sin gular value decomposition (SVD).