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Analysis of Image Using Discrete Cosine Transformation

Virendra Singh, Dr. Vineeta Saxena, Manini Singh

Abstract


Digital image processing remains a challenging domain of programming. There are several transforms that do image transformation. Image denoising aims at attenuating the noise while retaining the image content. Data (image) compression is the reduction or elimination of redundancy in data representation in order to achieve reduction in storage and communication cost. Many algorithms and VLSI architectures for the fast computation of DCT have been proposed .A discrete cosine transform (DCT) expresses a sequence of finitely many data points in terms of a sum of cosine functions oscillating at different frequencies. DCTs are important to numerous applications in science and engineering. I can perform discrete cosine transformation by different algorithms, in this paper we use pixels processing. In this paper we have implement method for image transformation, and analysis using discrete cosine transformation technique and develop results using matlab coding. In future the matlab code can be converted to VHDL code and implement on FPGA kit in order to develop ASIC(application specific IC) for image transformation and analysis. This will give a generalization to image processing.

Keywords


ASIC, Image Transformation, Discrete Cosine Transformation, VHDL

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References


Jensen, John R. (1986) Introductory Digital Image Processing. Prentice-Hall, New Jersey.

Russ, John C. (1995) The Image Processing Handbook. 2nd edition. CRC Press, Baca Raton.

Guoshen Yu, Guillermo Sapiro . DCT image denoising: a simple and effective image denoising algorithm. Image Processing On Line, 2011. DOI:10.5201/ipol.2011.ys-dct

Amir Averbuch, Danny Lazar, and Moshe Israeli,"Image Compression Using Wavelet Transform and Multiresolution Decomposition"IEEE Trans. on Image Processing, Vol. 5, No. 1, JANUARY 1996.

M. Antonini , M. Barlaud and I. Daubechies, "Image Coding using Wavelet Transform”,IEEE Trans. On Image Processing Vol.1, No.2, pp. 205 – 220, APRIL 1992.

Robert M. Gray,IEEE, and David L. Neuhoff, IEEE"Quantization", IEEE Trans. on Information Theory, Vol. 44, NO. 6,pp. 2325-2383, OCTOBER 1998.(invited paper).

Ronald A. DeVore, Bjorn Jawerth, and Bradley J. Lucier, Member,"Image Compression Through Wavelet Transform Coding" IEEE Trans. on Information Theory, Vol. 38. NO. 2, pp. 719-746, MARCH 1992.

http://bme.med.upatras.gr/improc/Histogram_Equaliz.htm.

Greg Ames,"Image Compression", Dec 07, 2002.

B.G. Lee, ― A new algoritm to compute the discrete cosine transform‖ ―IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-32, pp. 1243-1245, Dect.1984.

H.S Hou, ―A fast recursive algorithms for computing the discrete cosine transform, ―IEEE Trans. Acoust., Speech, Signal Processing, vol. ASSP-35, pp. 1455-1461, Oct.1987..

N.I Cho and S.U.Lee, ―DCT algorithms for VLSI parallel implementation,―IEEE Trans. Acoust., Speech, Signal Processing, vol 38. pp. 121-127,Jan.1990.

Nam Ik Cho, Sang Uk Lee ―Fast Algorithm and Implementation of 2-D Discrete Cosine Transform, ―IEEE Transaction on Circuits and Systems, Vol.38,No.3, March 1991.

N. Ahmed, T.Natarajan, and K.R. Rao, ―Discrete Cosine Transform, IEEE Trans. Commun., vol, COM-23, pp. 90-93, Jan. 1974

Nabeel Shirazi, Al Walters, and Peter Athanas ―Quantitative Analysis of Floating Point Arithmetic on FPGA Based Custom Computing Machines presented at the IEEE Symposium on FPGAs for Custom Machines, Napa Valley, California, April 1995.

M. Vetterli, ―Fast 2-D Discrete Cosine Transform, in Proc. ICASSP„85.Mar.1985.

srchttp://searchcioidmarket.techtarget.com/sDefinition/0,,sid183_gci212327,00.html.

http://encyclopedia.jrank.org/articles/pages/6760/Image-Compression-and-Coding.html

Bhawna Gautam(2010) Image Compression using Discrete Cosine Transform & Discrete Wavelet Transform.

nilerak.hatfieldgroup.com/English/NRAK/EO/html/rsbch15.

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