2011/08/31 by Asadollah Shahbahrami, Ramin Bahrampour, Shahbahrami, Asadollah +5
Computer Science · Mathematics · #68Uxx #Advanced Data Compression Techniques #Algorithms and Data Compression #FOS: Computer and information sciences #H.2 #Information Theory (cs.IT) #Multimedia (cs.MM) #Video Analysis and Summarization #acm:68Uxx #cs.IT #cs.MM #math.IT #msc:68Uxx
paper · pdf · doi:10.48550/arxiv.1109.0216
11 pages; http://airccse.org/journal/ijcsea/current.html International Journal of Computer Science, Engineering and Applications (IJCSEA) August 2011, Volume 1, Number 4
arxiv created 2011/08/31 · openalex publication_date 2011/08/31 · arxiv updated 2011/09/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.