New Model for Arithmetic Coding/decoding of Multilevel Images Based on a Cache Memory
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| Titel: | New Model for Arithmetic Coding/decoding of Multilevel Images Based on a Cache Memory |
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| Autoren: | Roberto Osorio, Javier D. Bruguera |
| Weitere Verfasser: | The Pennsylvania State University CiteSeerX Archives |
| Quelle: | http://www-gpaa.dec.usc.es/files/reports/1999/HPCG-99-001.ps.gz. |
| Publikationsjahr: | 1999 |
| Bestand: | CiteSeerX |
| Schlagwörter: | Paper category, 5.2 |
| Beschreibung: | In this work we present new methodologies for arithmetic encoding and decoding of multilevel images, achieving important improvements in cycle length and reducing complexity. Entropy coding methods should carry out operations of maintenance and search in tables, the size of which depends on the number of symbols of the alphabet. In this work we reduce the size of the table by introducing a new memory level, a cache. We obtain favourable speed-up and hardware savings, especially in the decoder. In some implementations the memory can be reduced to the cache, eliminating the RAM. Furthermore, the new scheme enables us to obtain excellent compression ratios. 1 Introduction Arithmetic coding (AC) is the state of the art in entropy compression [5] [7], outperforming the Huffman method [3]. Moreover, AC is adaptive. Adaptive methods [7] evolve as the statistical properties of data change. Every entropy coder is based on a statistical model, and special attention must be payed to reducing the. |
| Publikationsart: | text |
| Dateibeschreibung: | application/postscript |
| Sprache: | English |
| Relation: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.4785 |
| Verfügbarkeit: | http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.53.4785 http://www-gpaa.dec.usc.es/files/reports/1999/HPCG-99-001.ps.gz |
| Rights: | Metadata may be used without restrictions as long as the oai identifier remains attached to it. |
| Dokumentencode: | edsbas.C8BD71AC |
| Datenbank: | BASE |
Nájsť tento článok vo Web of Science | Abstract: | In this work we present new methodologies for arithmetic encoding and decoding of multilevel images, achieving important improvements in cycle length and reducing complexity. Entropy coding methods should carry out operations of maintenance and search in tables, the size of which depends on the number of symbols of the alphabet. In this work we reduce the size of the table by introducing a new memory level, a cache. We obtain favourable speed-up and hardware savings, especially in the decoder. In some implementations the memory can be reduced to the cache, eliminating the RAM. Furthermore, the new scheme enables us to obtain excellent compression ratios. 1 Introduction Arithmetic coding (AC) is the state of the art in entropy compression [5] [7], outperforming the Huffman method [3]. Moreover, AC is adaptive. Adaptive methods [7] evolve as the statistical properties of data change. Every entropy coder is based on a statistical model, and special attention must be payed to reducing the. |
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