Split field coding: low complexity error-resilient entropy coding for image compression

In this paper, we describe split field coding, an approach for low complexity, error-resilient entropy coding which splits code words into two fields: a variable length prefix and a fixed length suffix. Once a prefix has been decoded correctly, then the associated fixed length suffix is error-resilient, with bit errors causing no loss of code word synchronization and only a limited amount of distortion on the decoded value. When the fixed length suffixes are segregated to a separate block, this approach becomes suitable for use with a variety of methods which provide varying protection to different portions of the bitstream, such as unequal error protection or progressive ordering schemes. Split field coding is demonstrated in the context of a wavelet-based image codec, with examples of various error resilience properties, and comparisons to the rate-distortion and computational performance of JPEG 2000.

[1]  Gary J. Sullivan,et al.  The H.264/AVC Video Coding Standard [Standards in a Nutshell] , 2007 .

[2]  Michael W. Marcellin,et al.  JPEG2000: standard for interactive imaging , 2002, Proc. IEEE.

[3]  David S. Taubman,et al.  High performance scalable image compression with EBCOT. , 2000, IEEE transactions on image processing : a publication of the IEEE Signal Processing Society.

[4]  Nariman Farvardin,et al.  Subband Image Coding Using Entropy-Coded Quantization over Noisy Channels , 1992, IEEE J. Sel. Areas Commun..

[5]  Guillermo Sapiro,et al.  The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS , 2000, IEEE Trans. Image Process..

[6]  Thomas R. Fischer,et al.  Comparison of generalized Gaussian and Laplacian modeling in DCT image coding , 1995, IEEE Signal Processing Letters.

[7]  T. Moon.  Error Correction Coding: Mathematical Methods and Algorithms , 2005 .

[8]  Jorma Rissanen,et al.  Generalized Kraft Inequality and Arithmetic Coding , 1976, IBM J. Res. Dev..

[9]  I. Daubechies,et al.  Wavelet Transforms That Map Integers to Integers , 1998 .

[10]  Faouzi Kossentini,et al.  Reversible integer-to-integer wavelet transforms for image compression: performance evaluation and analysis , 2000, IEEE Trans. Image Process..

[11]  Ajay Luthra,et al.  Overview of the H.264/AVC video coding standard , 2003, IEEE Trans. Circuits Syst. Video Technol..

[12]  Nick G. Kingsbury,et al.  The EREC: an error-resilient technique for coding variable-length blocks of data , 1996, IEEE Trans. Image Process..

[13]  K A Birney,et al.  On the modeling of DCT and subband image data for compression , 1995, IEEE Trans. Image Process..

[14]  Ian H. Witten,et al.  Arithmetic coding for data compression , 1987, CACM.

[15]  Gary J. Sullivan,et al.  HD Photo: a new image coding technology for digital photography , 2007, SPIE Optical Engineering + Applications.

[16]  Robert J. Safranek,et al.  Signal compression based on models of human perception , 1993, Proc. IEEE.

[17]  D. Huffman.  A Method for the Construction of Minimum-Redundancy Codes , 1952 .

[18]  David S. Taubman,et al.  High performance scalable image compression with EBCOT , 1999, Proceedings 1999 International Conference on Image Processing (Cat. 99CH36348).

[19]  Edward R. Fiala,et al.  Data compression with finite windows , 1989, CACM.

[20]  David C. van Voorhis,et al.  Optimal source codes for geometrically distributed integer alphabets (Corresp.) , 1975, IEEE Trans. Inf. Theory.

[21]  S. Golomb.  Run-length encodings. , 1966 .

[22]  P. G. Sherwood,et al.  Progressive image coding on noisy channels , 1997, Proceedings DCC '97. Data Compression Conference.

[23]  Robert F. Rice,et al.  Some practical universal noiseless coding techniques , 1979 .