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Scintigraphic Image Coding Of Region Of Interest Based On Spiht Algorithm Using Global Thresholding And Huffman Coding

Authors: A. Seddiki; M. Djebbouri; D. Guerchi;

Scintigraphic Image Coding Of Region Of Interest Based On Spiht Algorithm Using Global Thresholding And Huffman Coding

Abstract

{"references": ["Z. Xiang, K. Ramachandran, M. T. Orchard and Y. Q. Zhing, A\ncomparative study of DCT and Wavelet based image coding, IEEE\nTransaction on Circuits Systems Video Technology, vol. 9, April 1999", "R. Sudhakar, M. R. Karthiga and S. Jayaraman, Image Compression\nusing Coding of Wavelet Coefficients-A Survey, ICGST-International\nJournal on Graphics, Vision and Image processing (GVIP), vol. 5, pp.\n25-38, 2005.", "F. Douak, R. Benzidi, and N. Benoudjit, Color image compression\nalgorithm based on the DCT transform combined to an adaptative block\nscanning, AEU-International Journal of Electronics and Communication,\nvol. 65, pp 16-26, Jan. 2011", "B.K.T. Ho, M.-J. Tsai, J. Wei, M. Ma, and P. Saipetch, Video\ncompression of coronary angiograms based on discrete wavelet\ntransform with block classification, IEEE Transactions on Medical\nImaging, Dec. 1996.", "M. D.Adams, and F. Kossentini, Performance Evaluation of reversible\ninteger to integer Wavelet Transforms for Image compression, IEEE\nTrans on image Processing, vol. 9, pp1010-1024, June 2000.H. Poor, An\nIntroduction to Signal Detection and Estimation. New York: Springer-\nVerlag, 1985, ch. 4.", "J. Wang, F. Zhang, Study of the image compression based on SPIHT\nalgorithm, IEEE International Conference on Intelligent Computing and\ncognitive Informatics(ICICCI), pp. 130-133, 2010.", "H. Zhu, C. Xiu, and D. Yang, An improvement SPIHT algorithm based\non Wavelet coefficient blocks for image coding, IEEE International\nConference on Computer Application and System Modeling (ICCASM),\nvol. 2, pp. 646-649, 2010.", "C. Xiu and H. Zhu, A modified SPIHT algorithm based on Coefficient\nblocks for Robust Image Transmission over Noisy Channel, IEEE\nInternational Symposium on information Science and Engeneering\n(ISISE), pp. 58-61, 2010.", "U. Qidawai, C. H. Chen, Digital Image Processing: An Algorithmic\nApproach with Matlab, CRC press, 2009.\n[10] A. Said, W. A. Pearlman, A new, Fast and Efficient Image Codec Based\non Set Partitioning in Hierarchical Trees, IEEE Transactions on Circuits\nand Systems for Video Technology, vol.6, pp. 1-16, 1996.\n[11] B. Chandra, B. Chanda, Color image compression based on block\ntruncation coding using pattern fitting principle, Pattern Recognition,\nvol. 40, pp. 2408-2417, Sept. 2007."]}

Medical imaging produces human body pictures in digital form. Since these imaging techniques produce prohibitive amounts of data, compression is necessary for storage and communication purposes. Many current compression schemes provide a very high compression rate but with considerable loss of quality. On the other hand, in some areas in medicine, it may be sufficient to maintain high image quality only in region of interest (ROI). This paper discusses a contribution to the lossless compression in the region of interest of Scintigraphic images based on SPIHT algorithm and global transform thresholding using Huffman coding.

Keywords

Huffman Coding, SPIHT Coding, Global Thresholding Transform, Region of Interest, Scintigraphic images.

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