Title :
Reduced-complexity waveform coding via alphabet partitioning
Author :
Said, Amis ; Pearlman, William A.
Author_Institution :
Fac. of Electr. Eng., State Univ. of Campinas, Brazil
Abstract :
We study the waveform coding problem where the data source symbols have a distribution that is simultaneously highly peaked and very long tailed-a situation when the source entropy is small, but the coding process must deal with a very large number of symbols. This type of problem can be found, for example, in the lossless compression of medical images. Those images are digitized with 10-12 bpp, and they are commonly quite smooth
Keywords :
computational complexity; entropy; image coding; reduced order systems; source coding; statistical analysis; alphabet partitioning; coding process; data source symbols; distribution; lossless compression; medical images; reduced-complexity waveform coding; source entropy; Biomedical imaging; Decoding; Entropy; Equations; Image coding; Tin;
Conference_Titel :
Information Theory, 1995. Proceedings., 1995 IEEE International Symposium on
Conference_Location :
Whistler, BC
Print_ISBN :
0-7803-2453-6
DOI :
10.1109/ISIT.1995.550360
