Open Science Research Excellence

Open Science Index

Commenced in January 2007 Frequency: Monthly Edition: International Publications Count: 29829


Select areas to restrict search in scientific publication database:
4004
Enhancement of Low Contrast Satellite Images using Discrete Cosine Transform and Singular Value Decomposition
Abstract:
In this paper, a novel contrast enhancement technique for contrast enhancement of a low-contrast satellite image has been proposed based on the singular value decomposition (SVD) and discrete cosine transform (DCT). The singular value matrix represents the intensity information of the given image and any change on the singular values change the intensity of the input image. The proposed technique converts the image into the SVD-DCT domain and after normalizing the singular value matrix; the enhanced image is reconstructed by using inverse DCT. The visual and quantitative results suggest that the proposed SVD-DCT method clearly shows the increased efficiency and flexibility of the proposed method over the exiting methods such as Linear Contrast Stretching technique, GHE technique, DWT-SVD technique, DWT technique, Decorrelation Stretching technique, Gamma Correction method based techniques.
Digital Object Identifier (DOI):

References:

[1] H. Demirel, C. Ozcinar, and G. Anbarjafari, "Satellite Image Contrast Enhancement Using Discrete Wavelet Transform and Singular Value Decomposition", IEEE Geosciences and Remote Sensing Letters, Vol. 7, No. 2, April 2010, pp. 333-337.
[2] R. C. Gonzalez, and R. E. Woods, "Digital Image Processing", Englewood Cliffs, NJ: Prentice-Hall, 2007.
[3] H. Demirel, G. Anbarjafari, and M. N. S. Jahromi, "Image Equalization Based On Singular Value Decomposition", Proceeding of IEEE Conference on Computer and Information Sciences, 2008, pp. 1-5.
[4] G. M. Hemes, S. Danaher, and A. Murray, "Characterization of Forestry Species - A Comparison Using Singular Value Decomposition (SVD) and Artificial Neural Networks (ANN)", Proceeding of IEEE Conference on image Processing and its Applications, 4-6 July 1995, pp. 815-819.
[5] P. S. Murty, and K.P. Rajesh, "A Robust Digital Image Watermarking Scheme Using Hybrid DWT-DCT-SVD Technique", International Journal of Computer Science and Network Security, Vol.10, No.1, October 2010, pp. 185-192.
[6] A. Sverdlovsk, S. Dexter, and A. M. Eskicioglu, "Robust DCT-SVD Domain Image Watermarking for Copyright Protection: Embedding Data in All Frequencies", Proceeding of 13th European Conference on signal processing, September 3-5, 2005, pp. 1-4.
[7] R. Reeves, and K. Kubik, "Benefits of Hybrid DCT Domain Image Matching. International Archives of Photogrammetric and Remote Sensing", Vol. 33, Part B3. Amsterdam 2000, pp. 771-778.
[8] C. M. Pun, and H. M. Zhu, "Image Segmentation Using Discrete Cosine Texture Feature", International Journal of Computers, Vol. 4, No. 1, 2010, pp. 19-26.
[9] A. Sagheer, N. Tsuruta, R. I. Taniguchi, and S. Maeda, "Hyper-Column Model vs. Fast DCT for Feature Extraction in Visual Arabic Speech Recognition", Proceeding of IEEE Conference on Signal Processing and Information Technology, 2005, pp. 761-766.
[10] T. A. Khaleel, "Enhancement of Spatial Structure of an Image by Using Texture Feature Extraction", Al-Rafidain Engineering, Vol.15, No.1, 2007, pp. 27-37.
[11] K. Su Kim, M. J. Lee, and H. K. Lee, "Blind Image Watermarking Scheme in DWT-SVD Domain", IEEE Intelligent Information Hiding and Multimedia Signal Processing, Vol. 2, No.2, 26-28 Nov. 2007, pp. 477-480.
[12] M. Azam, M. A. Anjum, M. Y. Javed, "Discrete Cosine Transform (DCT) Based Face Recognition in Hexagonal Images", Computer and Automation Engineering (ICCAE), Vol-2, 26-28 Feb. 2010, pp. 474 - 479.
[13] C. J. Christopher, M. Prabukumar, and A. Baskar, "Color Image Enhancement in Compressed DCT Domain", ICGST - GVIP Journal, Vol-10, 1, February 2010, pp. 31-38.
[14] C. Sanderson, and K. K. Paliwal, "Fast feature extraction method for robust face verification", Proceeding of IEEE Conference on Electronics Letter, Vol-38, No. 25, December 2002, pp. 1648-1650.
[15] G. Sorwar, A. Abraham, and L. S. Dooley "DCT Based Texture Classification Using Soft Computing Approach". Proceeding of 10th IEEE Conference on Fuzzy Systems, Vol-2, 2001, pp. 445-448.
[16] G. Sorwar, A. Abraham, and L. S. Dooley, "Texture Classification Based on DCT and Soft Computing", Proceeding of IEEE Conference on Fuzzy Systems, Dec. 2001, Vol-2, pp. 445-448.
[17] A. B. Watson, "Image Compression Using the Discrete Cosine Transform", Mathematica Journal, 1994, pp. 81-88.
[18] I. Hacihaliloglu and M. Kartal "DCT and Dwt Based Image Compression in Remote Sensing Images". Proceeding of IEEE Conference on Antennas and Propagation Society International Symposium, 2004, Vol-4, pp. 3856-3858.
[19] A. Sverdlov, S. Dexter, and M. A. Eskicioglu, "Robust DCT-SVD Domain Image Watermarking For Copyright Protection: Embedding Data In All Frequencies". Proceedings of ACM Digital Library on Multimedia and security, 2004.
[20] V.R. Ayangar, S.N Talbar, "A Novel DWT-SVD Based Watermarking Scheme", Proceeding of IEEE Conference on Multimedia Computing and Information Technology, (08 April 2010), pp. 105-108.
[21] http://lisamccluremaps.blogspot.com/2008_07_01_archive.html
Vol:13 No:07 2019Vol:13 No:06 2019Vol:13 No:05 2019Vol:13 No:04 2019Vol:13 No:03 2019Vol:13 No:02 2019Vol:13 No:01 2019
Vol:12 No:12 2018Vol:12 No:11 2018Vol:12 No:10 2018Vol:12 No:09 2018Vol:12 No:08 2018Vol:12 No:07 2018Vol:12 No:06 2018Vol:12 No:05 2018Vol:12 No:04 2018Vol:12 No:03 2018Vol:12 No:02 2018Vol:12 No:01 2018
Vol:11 No:12 2017Vol:11 No:11 2017Vol:11 No:10 2017Vol:11 No:09 2017Vol:11 No:08 2017Vol:11 No:07 2017Vol:11 No:06 2017Vol:11 No:05 2017Vol:11 No:04 2017Vol:11 No:03 2017Vol:11 No:02 2017Vol:11 No:01 2017
Vol:10 No:12 2016Vol:10 No:11 2016Vol:10 No:10 2016Vol:10 No:09 2016Vol:10 No:08 2016Vol:10 No:07 2016Vol:10 No:06 2016Vol:10 No:05 2016Vol:10 No:04 2016Vol:10 No:03 2016Vol:10 No:02 2016Vol:10 No:01 2016
Vol:9 No:12 2015Vol:9 No:11 2015Vol:9 No:10 2015Vol:9 No:09 2015Vol:9 No:08 2015Vol:9 No:07 2015Vol:9 No:06 2015Vol:9 No:05 2015Vol:9 No:04 2015Vol:9 No:03 2015Vol:9 No:02 2015Vol:9 No:01 2015
Vol:8 No:12 2014Vol:8 No:11 2014Vol:8 No:10 2014Vol:8 No:09 2014Vol:8 No:08 2014Vol:8 No:07 2014Vol:8 No:06 2014Vol:8 No:05 2014Vol:8 No:04 2014Vol:8 No:03 2014Vol:8 No:02 2014Vol:8 No:01 2014
Vol:7 No:12 2013Vol:7 No:11 2013Vol:7 No:10 2013Vol:7 No:09 2013Vol:7 No:08 2013Vol:7 No:07 2013Vol:7 No:06 2013Vol:7 No:05 2013Vol:7 No:04 2013Vol:7 No:03 2013Vol:7 No:02 2013Vol:7 No:01 2013
Vol:6 No:12 2012Vol:6 No:11 2012Vol:6 No:10 2012Vol:6 No:09 2012Vol:6 No:08 2012Vol:6 No:07 2012Vol:6 No:06 2012Vol:6 No:05 2012Vol:6 No:04 2012Vol:6 No:03 2012Vol:6 No:02 2012Vol:6 No:01 2012
Vol:5 No:12 2011Vol:5 No:11 2011Vol:5 No:10 2011Vol:5 No:09 2011Vol:5 No:08 2011Vol:5 No:07 2011Vol:5 No:06 2011Vol:5 No:05 2011Vol:5 No:04 2011Vol:5 No:03 2011Vol:5 No:02 2011Vol:5 No:01 2011
Vol:4 No:12 2010Vol:4 No:11 2010Vol:4 No:10 2010Vol:4 No:09 2010Vol:4 No:08 2010Vol:4 No:07 2010Vol:4 No:06 2010Vol:4 No:05 2010Vol:4 No:04 2010Vol:4 No:03 2010Vol:4 No:02 2010Vol:4 No:01 2010
Vol:3 No:12 2009Vol:3 No:11 2009Vol:3 No:10 2009Vol:3 No:09 2009Vol:3 No:08 2009Vol:3 No:07 2009Vol:3 No:06 2009Vol:3 No:05 2009Vol:3 No:04 2009Vol:3 No:03 2009Vol:3 No:02 2009Vol:3 No:01 2009
Vol:2 No:12 2008Vol:2 No:11 2008Vol:2 No:10 2008Vol:2 No:09 2008Vol:2 No:08 2008Vol:2 No:07 2008Vol:2 No:06 2008Vol:2 No:05 2008Vol:2 No:04 2008Vol:2 No:03 2008Vol:2 No:02 2008Vol:2 No:01 2008
Vol:1 No:12 2007Vol:1 No:11 2007Vol:1 No:10 2007Vol:1 No:09 2007Vol:1 No:08 2007Vol:1 No:07 2007Vol:1 No:06 2007Vol:1 No:05 2007Vol:1 No:04 2007Vol:1 No:03 2007Vol:1 No:02 2007Vol:1 No:01 2007