Title :
New methods for lossless image compression using arithmetic coding
Author :
Howard, Paul G. ; Vitter, Jeffrey Scott
Author_Institution :
Dept. of Comput. Sci., Brown Univ., Providence, RI, USA
Abstract :
Lossless text compression methods involve some form of moderately high-order exact string matching. However, this work cannot easily be carried over to lossless image compression, because images are two-dimensional and (more important) essentially quantized analog data. A better plan is to find and encode as much of the image structure of the data as possible, and then to encode efficiently the unstructured, noisy residual. In three steps the authors predict the value of each pixel, model the error of the prediction, and encode the error of the prediction. Having a probabilistic model for the errors, they can use arithmetic coding to encode the errors efficiently with respect to the model
Keywords :
data compression; encoding; error analysis; filtering and prediction theory; picture processing; arithmetic coding; image structure; lossless image compression; noisy residual; prediction error modelling; probabilistic model; Computer science; Digital arithmetic; Image coding; Image reconstruction; Iterative decoding; NASA; Predictive models;
Conference_Titel :
Data Compression Conference, 1991. DCC '91.
Conference_Location :
Snowbird, UT
Print_ISBN :
0-8186-9202-2
DOI :
10.1109/DCC.1991.213355