  Compression is a technique to reduce the quantity of data without excessively
reducing the quality of the multimedia data. The transition and storing of
compressed multimedia data is much faster and more efficient than original
uncompressed multimedia data. There are various techniques and standards for
multimedia data compression, especially for image compression such as the JPEG
and JPEG2000 standards. These standards consist of different functions such as
color space conversion and entropy coding. Arithmetic and Huffman coding are
normally used in the entropy coding phase. In this paper we try to answer the
following question. Which entropy coding, arithmetic or Huffman, is more
suitable compared to other from the compression ratio, performance, and
implementation points of view? We have implemented and tested Huffman and
arithmetic algorithms. Our implemented results show that compression ratio of
arithmetic coding is better than Huffman coding, while the performance of the
Huffman coding is higher than Arithmetic coding. In addition, implementation of
Huffman coding is much easier than the Arithmetic coding.
