Name
Abstract | ||
|---|---|---|
The main difficulty to implement modern image coding systems in a GPU is that the algorithms employed in the core of the coding scheme are inherently sequential. We recently proposed bitplane image coding with parallel coefficient processing (BPC-PaCo), a coding scheme that, contrarily to most systems, permits the processing of multiple coefficients of the image in parallel. This enables the use of SIMD computing, ideal for its implementation in a GPU. This paper introduces and evaluates the GPU implementation of BPC-PaCo employing two different strategies that tradeoff computational throughput and compression efficiency. The proposed implementation is compared to the best CPU and GPU implementations of JPEG2000, the state-of-the-art image compression standard. Experimental results indicate that BPC-PaCo achieves a computational throughput that is an order of magnitude superior to that achieved with such implementations with a small reduction in coding efficiency. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1109/HiPC.2015.12 | HiPC |
Keywords | Field | DocType |
image coding, parallel architectures, SIMD computing, GPU | Algorithmic efficiency,Computer science,Parallel computing,Transform coding,SIMD,Real-time computer graphics,General-purpose computing on graphics processing units,Digital image processing,Image compression,Context-adaptive binary arithmetic coding | Conference |
Citations | PageRank | References |
1 | 0.36 | 6 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pablo Enfedaque | 1 | 8 | 1.60 |
| Francesc Auli-Llinas | 2 | 42 | 10.68 |
| Juan Carlos Moure | 3 | 82 | 13.31 |