Name
Abstract | ||
|---|---|---|
Next generations of still image codecs should not only have to be efficient in terms of compression ratio, but also propose other functionalities such as scalability, lossy and lossless abilities, region of interest coding, etc. In previous works, we have proposed the LAR compression method covering these requirements. In particular, the Interleaved S+P scheme offers an efficient mean to compress images, especially in the medical field. In this paper, two classification methods are proposed in order to increase the compression ratio of the coder. The first one is based on a spatial context, the second one takes into account the local activity of the picture. Results are then discussed and compared to the state of the art, thus revealing high compression performances of our coding solution. |
Year | Venue | Keywords |
|---|---|---|
2008 | Lausanne | image classification,image coding,medical image processing,LAR compression method,inter-coefficient classification methods,interleaved S+P scalable coding scheme,still image codecs |
Field | DocType | ISSN |
Block Truncation Coding,Lossy compression,Computer science,Context-adaptive variable-length coding,Color Cell Compression,Algorithm,Theoretical computer science,Data compression,Image compression,Context-adaptive binary arithmetic coding,Lossless compression | Conference | 2219-5491 |
Citations | PageRank | References |
1 | 0.43 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| François Pasteau | 1 | 39 | 6.87 |
| Marie Babel | 2 | 66 | 12.93 |
| Olivier Déforges | 3 | 176 | 41.52 |
| Laurent Bédat | 4 | 29 | 5.51 |