Title :
Symbol mapping and context filtering for lossless image compression
Author_Institution :
Dept. of Electron. Eng., La Trobe Univ., Bundoora, Vic., Australia
Abstract :
Key building blocks of lossless image compression algorithms include adaptive prediction, context-based error feedback and adaptive entropy coding. This paper presents a new algorithm which includes two other building blocks-symbol mapping and context filtering. Experimental results show that the compression performance of the proposed algorithm is very close to that of CALIC and is better than that of LOGO and S+P. It is different from CALIC in the following aspects: (1) an adaptive median-FIR predictor, (2) a new error representation scheme using symbol mapping, (3) a different context calculation scheme for the prediction error, and (4) a new context filtering scheme
Keywords :
FIR filters; adaptive filters; data compression; image coding; median filters; prediction theory; adaptive median-FIR predictor; compression performance; context filtering; error representation scheme; lossless image compression; prediction error; symbol mapping; Adaptive filters; Biomedical imaging; Compression algorithms; Decoding; Entropy coding; Feedback; Filtering; Image coding; Prediction algorithms; Quantization;
Conference_Titel :
Image Processing, 1998. ICIP 98. Proceedings. 1998 International Conference on
Conference_Location :
Chicago, IL
Print_ISBN :
0-8186-8821-1
DOI :
10.1109/ICIP.1998.723554
