Name
Title | ||
|---|---|---|
ON THE DESIGN OF AN IMAGE COMPRESSION SCHEME BASED UPON A PRIORI KNOWLEDGE ABOUT IMAGING SYSTEM AND IMAGE STATISTICS |
Abstract | ||
|---|---|---|
This contribution is about the design of an image compression scheme for near loss-less image compression of a restricted class of images and a specific application. The images are digital diagnostic X-ray images of the coronary vessels of the human heart. This paper proposes a novel compression scheme with a compression ratio of 8 - 10 with preservation of the diagnostic image quality. Central in our approach is the amount of information a trained and highly skilled observer i.e. the cardiologist is able discern at a given exposure and thus quantum noise level. The physics of the image detection process together with the a priori knowledge of the imaging system are the basis of the image statistics. Relevant elements of the human visual system complete the stochastic characterization of imaging process whereon the compression scheme is based. |
Year | Venue | Field |
|---|---|---|
1996 | EUSIPCO | Computer vision,Texture compression,Feature detection (computer vision),Image quality,Image processing,Artificial intelligence,Image restoration,Statistics,Data compression,Fractal transform,Image compression,Mathematics |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| C. H. Slump | 1 | 9 | 3.70 |
| F. J. de Bruijn | 2 | 0 | 0.34 |
| P. J. A. Hagendoorn | 3 | 0 | 0.34 |