Highly Scalable, Reversible and Embedded Image Compression System
Authors: Federico Pérez González, Iñaki Goiricelaia Ordorika, Pedro Iriondo Bengoa
Abstract:
A new method for low complexity image coding is presented, that permits different settings and great scalability in the generation of the final bit stream. This coding presents a continuoustone still image compression system that groups loss and lossless compression making use of finite arithmetic reversible transforms. Both transformation in the space of color and wavelet transformation are reversible. The transformed coefficients are coded by means of a coding system in depending on a subdivision into smaller components (CFDS) similar to the bit importance codification. The subcomponents so obtained are reordered by means of a highly configure alignment system depending on the application that makes possible the re-configure of the elements of the image and obtaining different levels of importance from which the bit stream will be generated. The subcomponents of each level of importance are coded using a variable length entropy coding system (VBLm) that permits the generation of an embedded bit stream. This bit stream supposes itself a bit stream that codes a compressed still image. However, the use of a packing system on the bit stream after the VBLm allows the realization of a final highly scalable bit stream from a basic image level and one or several enhance levels.
Keywords: Image compression, wavelet transform, highlyscalable, reversible transform, embedded, subcomponents.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1060559
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1415References:
[1] J.M. Shapiro, "Embedded image coding using zerotrees of wavelet coefficients" IEEE transactions of Signal Procesing, vol. 41, pp. 3445- 3462, Dec. 1993.
[2] A. Said and W.A. Pearlman, "A new, fast, and efficient image codec based on set partitioning in hierarchical trees" IEEE Transactions on Circuits and Systems for Video Technology, vol. 6, pp. 243-250, Jun. 1996.
[3] M.P. Boliek, M.J. Gormish, E.L. Schwartz and A.F. Keith, "RICOH CREW Image Compression Standard" RICOH Silicon Valley, Inc., Mar. 1999
[4] ISO/IEC, ITU-T, "Information technology - JPEG2000 image coding system" ITU-T Rec. T800, ISO/IEC 154444-1, 1999.
[5] ISO/IEC, "Information technology - Generic coding of audio-visual objects: part 2 visual" ISO/IEC 14486-2, 2003.
[6] S. Mallat, "A wavelet tour of signal processing. Second edition", Academic Press, San Diego, 1999
[7] R. Calderbank, I. Daubechies, W. Sweldens and B.L. Yeo, "Wavelet transforms that map integers to integers", Journal of Applications and Components, vol. 5, 1998
[8] W. Sweldens, "The lifting scheme: Construction of second generation wavelets", SIAM Mathematical Analisys, vol. 29. No. 2, pp. 511-546, 1997
[9] M.D. Adams and F. Kossentini, "Reversible integer-to-integer wavelet transform for image compression: Performance, evaluation and analysis" IEEE Transactions on Image Processing, vol. 9, no. 6, Jun. 2000.
[10] S. Sahni, B.C. Vemuri, F. Chen, C. Kapoor, C. Leonard, J. Fitzsimmons, "State of the art lossless image compression algorithms", IEEE Proceedings of the International Conference on Image Processing, Chicago, Illinois, pp. 948-952, Nov. 1998