Abstract
A near-lossless image compression scheme is presented. It is essentially a DPCM system with a mechanism incorporated to minimize the entropy of the quantized prediction error sequence. With a 'near-lossless' criterion of no more than a d gray level error for each pixel, where d is a small non-negative integer, trellises describing all allowable quantized prediction error sequences are constructed. A set of 'contexts' is defined for the conditioning prediction error model and an algorithm that produces minimum entropy conditioned on the contexts is presented. Finally, experimental results are given.
| Original language | English (US) |
|---|---|
| Pages | 298-301 |
| Number of pages | 4 |
| State | Published - 1996 |
| Event | Proceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3) - Washington, DC, USA Duration: Oct 23 1995 → Oct 26 1995 |
Other
| Other | Proceedings of the 1995 IEEE International Conference on Image Processing. Part 3 (of 3) |
|---|---|
| City | Washington, DC, USA |
| Period | 10/23/95 → 10/26/95 |
ASJC Scopus subject areas
- Hardware and Architecture
- Computer Vision and Pattern Recognition
- Electrical and Electronic Engineering