Common image compression standards are usually based on frequency transform such as Discrete Cosine Transform or Wavelets. We present a different approach for loss-less image compression, it is based on combinatorial transform. The main transform is Burrows Wheeler Transform (BWT) which tends to reorder symbols according to their following context. It becomes a promising compression approach based on contextmodelling. BWT was initially applied for text compression software such as BZIP2 ; nevertheless it has been recently applied to the image compression field. Compression scheme based on Burrows Wheeler Transform is usually lossless ; therefore we imple-ment this algorithm in medical imaging in order to reconstruct every bit. Many vari-ants of the three stages which form the original BWT-based compression scheme can be found in the literature. We propose an analysis of the more recent methods and the impact of their association. Then, we present several compression schemes based on this transform which significantly improve the current standards such as JPEG2000and JPEG-LS. In the final part, we present some open problems which are also further research directions
| Identifer | oai:union.ndltd.org:CCSD/oai:tel.archives-ouvertes.fr:tel-00750879 |
| Date | 29 June 2011 |
| Creators | Syahrul, Elfitrin |
| Publisher | Université de Bourgogne |
| Source Sets | CCSD theses-EN-ligne, France |
| Language | English |
| Detected Language | English |
| Type | PhD thesis |
Page generated in 0.0019 seconds