{"title":"Reversible, Embedded and Highly Scalable Image Compression System","authors":"Federico P\u00e9rez Gonz\u00e1lez, I\u00f1aki Goirizelaia Ordorika, Pedro Iriondo Bengoa","volume":19,"journal":"International Journal of Electronics and Communication Engineering","pagesStart":1527,"pagesEnd":1532,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/7638","abstract":"In this work a new method for low complexity\r\nimage coding is presented, that permits different settings and great\r\nscalability in the generation of the final bit stream. This coding\r\npresents a continuous-tone still image compression system that\r\ngroups loss and lossless compression making use of finite arithmetic\r\nreversible transforms. Both transformation in the space of color and\r\nwavelet transformation are reversible. The transformed coefficients\r\nare coded by means of a coding system in depending on a\r\nsubdivision into smaller components (CFDS) similar to the bit\r\nimportance codification. The subcomponents so obtained are\r\nreordered by means of a highly configure alignment system\r\ndepending on the application that makes possible the re-configure of\r\nthe elements of the image and obtaining different importance levels\r\nfrom which the bit stream will be generated. The subcomponents of\r\neach importance level are coded using a variable length entropy\r\ncoding system (VBLm) that permits the generation of an embedded\r\nbit stream. This bit stream supposes itself a bit stream that codes a\r\ncompressed still image. However, the use of a packing system on the\r\nbit stream after the VBLm allows the realization of a final highly\r\nscalable bit stream from a basic image level and one or several\r\nimprovement levels.","references":"[1] J.M. Shapiro, \"Embedded image coding using zerotrees of wavelet\r\ncoefficients\" IEEE transactions of Signal Procesing, vol. 41, pp. 3445-\r\n3462, Dec. 1993.\r\n[2] A. Said and W.A. Pearlman, \"A new, fast, and efficient image codec\r\nbased on set partitioning in hierarchical trees\" IEEE Transactions on\r\nCircuits and Systems for Video Technology, vol. 6, pp. 243-250, Jun.\r\n1996.\r\n[3] M.P. Boliek, M.J. Gormish, E.L. Schwartz and A.F. Keith, \"RICOH\r\nCREW Image Compression Standard\" RICOH Silicon Valley, Inc., Mar.\r\n1999\r\n[4] ISO\/IEC, ITU-T, \"Information technology - JPEG2000 image coding\r\nsystem\" ITU-T Rec. T800, ISO\/IEC 154444-1, 1999.\r\n[5] ISO\/IEC, \"Information technology - Generic coding of audio-visual\r\nobjects: part 2 visual\" ISO\/IEC 14486-2, 2003.\r\n[6] S. Mallat, \"A wavelet tour of signal processing. Second edition\",\r\nAcademic Press, San Diego, 1999\r\n[7] R. Calderbank, I. Daubechies, W. Sweldens and B.L. Yeo, \"Wavelet\r\ntransforms that map integers to integers\", Journal of Applications and\r\nComponents, vol. 5, 1998\r\n[8] W. Sweldens, \"The lifting scheme: Construction of second generation\r\nwavelets\", SIAM Mathematical Analisys, vol. 29. No. 2, pp. 511-546,\r\n1997\r\n[9] M.D. Adams and F. Kossentini, \"Reversible integer-to-integer wavelet\r\ntransform for image compression: Performance, evaluation and analysis\"\r\nIEEE Transactions on Image Processing, vol. 9, no. 6, Jun. 2000.\r\n[10] S. Sahni, B.C. Vemuri, F. Chen, C. Kapoor, C. Leonard, J. Fitzsimmons,\r\n\"State of the art lossless image compression algorithms\", IEEE\r\nProceedings of the International Conference on Image Processing,\r\nChicago, Illinois, pp. 948-952, Nov. 1998","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 19, 2008"}