2 research outputs found
Analysis of Arithmetic Coding for Data Compression
Arithmetic coding, in conjunction with a suitable probabilistic model, can pro-
vide nearly optimal data compression. In this article we analyze the e ect that
the model and the particular implementation of arithmetic coding have on the
code length obtained. Periodic scaling is often used in arithmetic coding im-
plementations to reduce time and storage requirements; it also introduces a
recency e ect which can further a ect compression. Our main contribution is
introducing the concept of weighted entropy and using it to characterize in an
elegant way the e ect that periodic scaling has on the code length. We explain
why and by how much scaling increases the code length for les with a ho-
mogeneous distribution of symbols, and we characterize the reduction in code
length due to scaling for les exhibiting locality of reference. We also give a
rigorous proof that the coding e ects of rounding scaled weights, using integer
arithmetic, and encoding end-of- le are negligible