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Pàgina inicial > Articles > Articles publicats > Probability models for highly parallel image coding architecture |
Data: | 2023 |
Resum: | A key aspect of image coding systems is the probability model employed to code the data. The more precise the probability estimates inferred by the model, the higher the coding efficiency achieved. In general, probability models adjust the estimates after coding every new symbol. The main difficulty to apply such a strategy to a highly parallel coding engine is that many symbols are coded simultaneously, so the probability adaptation requires a different approach. The strategy employed in previous works utilizes stationary estimates collected a priori from a training set. Its main drawback is that statistics are dependent of the image type, so different images require different training sets. This work introduces two probability models for a highly parallel architecture that, similarly to conventional systems, adapt probabilities while coding data. One of the proposed models estimates probabilities through a finite state machine, while the other employs the statistics of already coded symbols via a sliding window. Experimental results indicate that the latter approach improves the performance achieved by the other models, including that of JPEG2000 and High Throughput JPEG2000, at medium and high rates with only a slight increase in computational complexity. |
Ajuts: | Agencia Estatal de Investigación RTI2018-095287-B-I00 Ministerio de Ciencia e Innovación PID2021-125258OB-I00 Agència de Gestió d'Ajuts Universitaris i de Recerca 2018-BP-00008 Agència de Gestió d'Ajuts Universitaris i de Recerca 2017/SGR-463 European Commission 801370 |
Nota: | Altres ajuts: acords transformatius de la UAB |
Drets: | Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades. |
Llengua: | Anglès |
Document: | Article ; recerca ; Versió publicada |
Matèria: | Image coding ; Parallel computing ; Entropy coding ; Probability models |
Publicat a: | Signal Processing: Image Communication, Vol. 112 (March 2023) , art. 116914, ISSN 0923-5965 |
8 p, 511.4 KB |