International Journal of Modern Education and Computer Science (IJMECS)
IJMECS Vol. 6, No. 4, 8 Apr. 2014
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Performance Evaluation of DWT Compared to DCT for Compression Biomedical Image
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Author(s)
Beladgham Mohammed
1,*
Habchi Yassine
1
Moulay Lakhdar Abdelmouneim
1
Bassou Abdesselam
1
Taleb-Ahmed Abdelmalik
1
Index Terms
Image compression, DWT, DCT, EZW
Abstract
The image compression has for objective to reduce the volume of data required by the encoding of image, for applications of transmission or saving. For this we use the redundancies which exists within an image (a pixel has a good chance of having a luminance close to those of its neighbors) or between successive images in a sequence. We limit ourselves to the exploitation of redundancies within an image and we will work on gray level images of size 512x512. For image coding we chose an encoder based on progressive coding of data, coder is EZW (EMBEDDED WAVELET ZeroTree ENCODING, Shapiro 1993), the basis of this encoder a comparison is made between two types of transforms DWT (DISCREET WAVELETS TRANSFORM) and DCT (DISCRETE COSINE TRANSFORM) just to have the type of transformation that allows us to have a better visual quality of the image after decomposition. . Visual quality image is judged by two important devaluation parameters PSNR and MSSIM.
Cite This Paper
Beladgham Mohammed, Habchi Yassine, Moulay Lakhdar Abdelmouneim, Bassou Abdesselam, Taleb-Ahmed Abdelmalik, "Performance Evaluation of DWT Compared to DCT for Compression Biomedical Image", International Journal of Modern Education and Computer Science (IJMECS), vol.6, no.4, pp.9-15, 2014. DOI:10.5815/ijmecs.2014.04.02
Reference
[1]B.Aoued, "Technique de compression d’images", Office des publications universitaires, Alger, 2004.
[2]ABRY P, SELLAN F "The wavelet-based synthesis for Fractal Brownian Motion proposed by F.Sellan and Y.Meyer-emarks and fast implementation", Applied and comp. Harmonic An., Vol.3,1996.
[3]ABRAMOVIC F, BAILEY T, C, SAPATINAS T, "wavelet analysis and its statistical applications", The Statistician, vol.49, 2000.
[4]John Watkinson, " La réduction de débit en audio et vidéo", éditions eyrolles, ISBN 2-22-09814-6, 1998.
[5]WITTENS I, NEAL R, CLEARY J, "Arithmitic coding for data compression", comm.of the ACM, vol.30,n°6, 1987.
[6]HOWARD P.G, WITTER G.S,"Practical Implimentations of arithmetic coding in image and text compression", kluwer academic publisher, 1992.
[7]HUFFMAN D.A, "A method for the construction of minimum redundancy codes", Proc. Of IRE, n°40, 1952.
[8]W.S. Geisler, M.S. Banks, "Visual Performance, Handbook of Optics", Vol. 1, McGraw-Hill, NY, USA, 1995.
[9]A.B. Watson, L.B. Kreslake, "Measurement of Visual Impairment Scales for Digital Video, Human Vision and Electronic Imaging", Conference, San Jose, CA, USA, SPIE Vol. 4299, Jan. 2001, 2001, pp. 79 – 89.
[10]Eugene K. Yen and Roger G. Johnston, "The Ineffectiveness of the Correlation Coefficient for Image Comparisons", Vulnerability Assessment Team, Los Alamos National Laboratory, MS J565, Los Alamos, New Mexico 87545.