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Performance Evaluation of Wavelet and Contourlet based Joint Medical Image Compression

Divya Mohandass, Dr. J. Janet

Abstract


Medical images are very crucial in providing a good diagnosis. It becomes imperative for these medical images to be processed. In this paper, we present a lossless image coder based on wavelet transform. The efficiency of wavelet transform in representing smooth edges present in medical images has been proved in literature. It has good localization properties in spatial and frequency domain. Ostu‘s global thresholding algorithm and Huffman encoding are applied to the wavelet transformed image. This encoding algorithm has been applied to CT, MRI images. The drawback in wavelet when representing edges has been overcome by the contourlet transform. The proposed joint image compression algorithm was applied to the contourlet transformed image. Experimental results indicate a comparative approach of the proposed system between the wavelet and the contourlet transformed image. The results obtained were appreciable in terms of compression ratio and PSNR values.

Keywords


Lossless Compression, Global Thresholding, Huffman Encoding, Contourlet, Wavelet

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References


Clunie, DA, Lossless compression of gray scale medical images — Effectiveness of traditional and state of the art approaches, SPIE International Conference on Medical Imaging, San DIEGO, CA, Feb 2000, pp. 74–84.

A.Bilgin, P.J Sementelli, F.Sheng, M.Marcellin, Scalable Image Coding using reversible integer wavelet, IEEE Transactions on Image Processing ,1972–1977.

Deever.A.D, Hemami.S.S, Lossless image compression with projection based and adaptive reversible integer wavelet transforms ,IEEE Transactions on Image processing 12(05) (2003), pp. 489–499.

Adams.M.D, Kossentini.F, Reversible integer to integer wavelet transforms.

Da-Zeng Tian, Ming-Hu Ha, Applications Of Wavelet Transforms in Medical Image Processing, Proceedings of the Third International Conference on Machine Learning and Cybernetics, August 2004, pp. 1816–1821.

V.Velisavljevic, P.L.Dragotti, M.Vetterli, ―Directional Wavelet Transforms and Frames‖, Proceedings of IEEE International Conference on Image Processing (ICIP2002), vol. 3, pp. 589–592.

S.M.Ramesh & Dr.A.Shanmugam, "Medical Image Compression using Wavelet Decomposition for Prediction Method",(IJCSIS) International Journal of Computer Science and Information Security, Vol. 7, No. 1, 2010, pp. 262–265.

S.Esakkirajan, T.Veerakumar, V. Senthil Murugan, R.Sudhakar, ―Image Compression using Contourlet transform and Multistage Vector Quantisation‖, ICGST, GVIP Special Issue on Image Compression, 2007.

Negar Riazifar and Mehran Yazdi, Effectiveness of Contourlet vs. Wavelet Transform on Medical Image Compression: a Comparative Study, WASET, 49 2009, pp. 837–841.

Schomer D.F, Elekes, Hazle.J.D, Huffman.J.C, Thompson.S.K, Persons.K.R., Wavelet Compression Of Medical Images, Radiology, Vol. 206, No.3, pp. 599–607.

Kyriakopoulos.K.G and ParishD.J, A live system for wavelet compression of high speed computer network measurements, Proceedings of PAM(2007), Vol. 4427, LNCS, pp. 241–244.

Otsu.N., A threshold selection method from gray-level histograms. IEEE Transactions on Systems Man, Cybernet, pp. 62–66.

Said.A and Pearlman.W.A, ―A new, fast and efficient image codec based on set partitioning in Hierarchical trees,‖ IEEE Trans. Circuits Syst. VideoTechnol., Vol. 6, No. 3, pp. 243–250.

Bouridane.A, Khelifi.F, Amira.Kurugollu, Boussakta.S, A very low bit-rate embedded color image coding with SPIHT, Proceedings IEEE International Conference Acoust.Speecg Signal Process, 4(2004), pp. 689–692.

J.Janet, Divya Mohandass, S.Meenalosini, ―Lossless compression techniques for medical images in Telemedicine‖, Advances In Telemedicine, INTECH, Austria.

Divya Mohandass, J.Janet, S.Meenalosini, ―Joint Medical Image Compression based on Wavelets‖, Proceedings of ICST 2011, Veltech Dr.RR &Dr.SR Technical University, pp. 74–77.


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