Commenced in January 2007
Paper Count: 30169
Effective Context Lossless Image Coding Approach Based on Adaptive Prediction
Abstract:In the paper an effective context based lossless coding technique is presented. Three principal and few auxiliary contexts are defined. The predictor adaptation technique is an improved CoBALP algorithm, denoted CoBALP+. Cumulated predictor error combining 8 bias estimators is calculated. It is shown experimentally that indeed, the new technique is time-effective while it outperforms the well known methods having reasonable time complexity, and is inferior only to extremely computationally complex ones.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1084240Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1071
 G. Deng, Symbol mapping and context filtering techniques for lossless image compression, Proceedings of IEEE 1998 International Conference on Image Processing, v.1, pp. 526-529, Chicago, USA, Oct. 1998.
 F. Golchin, K. K. Paliwal, A lossless image coder with context classification, adaptive prediction and adaptive entropy coding, Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, Seattle, Washington, USA, May 1998, pp. 2545- 2548.
 Lih-Jen Kau, Yuan-Pei Lin, Lossless image coding using a switching predictor with run-length encodings, Proceedings of IEEE International Conference on Multimedia and Expo, June 2004, vol. 2, pp. 1155-1158.
 M. Marcellin, M. Gormish, A. Bilgin, M. Boliek, An Overview of JPEG- 2000, Proceedings of Data Compression Conference, Snowbird, Utah, March 2000, pp. 523-541.
 S. Marusic, G. Deng, Adaptive prediction for lossless image compression, Signal Processing: Image Communications, May 2002, vol. 17, pp. 363-372.
 I. Matsuda, N. Ozaki, Y. Umezu, S. Itoh, Lossless coding using Variable Blok-Size adaptive prediction optimized for each image, Proceedings of EUSIPCO-05, (CDROM), September 2005.
 B. Meyer, P. Tischer, TMWLego - An Object Oriented Image Modelling Framework, Proceedings of Data Compression Conference 2001, pp. 504.
 K. Sayood, Introduction to Data Compression, 2nd edition, Morgan Kaufmann Publ., 2002.
 T. Seemann, P. Tisher, B. Meyer, History-Based Blending of Image Sub- Predictors, Proceedings of Picture Coding Symp., Berlin, Germany, 1997, pp. 147-151.
 T. Strutz, Context-Based Adaptive Linear Prediction for Lossless Image Coding, 4th International ITG Conference on Source and Channel Coding, Berlin, Germany, 28-30 January, 2002, pp. 105-109.
 C. Topal, ├û. N. Gerek, Pdf sharpening for multichannel predictive coders, Proceedings of EUSIPCO-06 CD, Sept. 2006.
 G. Ulacha, R. Stasiński, A new context lossless image coding algorithm based on adaptive context arithmetic coder, Proceedings of 15th International Workshop on Systems, Signals & Image Processing - IWSSIP 2008, Bratislava, Slovak Republic 2008, pp. 45-48.
 G. Ulacha, R. Stasiński, New simple context-based predictive technique for lossless image compression, Proceedings of EUSIPCO-07 (CDROM), Poznań, Poland, September 2007, pp. 990-993.
 M. J. Weinberger, G. Seroussi, G. Sapiro, LOCO-I: A low complexity, context-based, lossless image compression algorithm. Proceedings of Data Compression Conference, March-April 1996, Snowbird, Utah, pp. 140-149.
 M. J. Weinberger, G. Seroussi, G. Sapiro ÔÇ×LOCO-I: Lossless Image Compression Algorithm: Principles and Standardization into JPEG-LS", IEEE Trans. on Image Processing, vol. 9, No. 8, August 2000, pp. 1309- 1324.
 X. Wu, N. D. Memon ÔÇ×CALIC - A Context Based Adaptive Lossless Image Coding Scheme", IEEE Trans. on Communications, May 1996, vol. 45, pp. 437-444.
 H. Ye, A study on lossless compression of greyscale images, PhD thesis, Department of Electronic Engineering, La Trobe University, October 2002.