Abstract
Most compression algorithms are desired for minimizing a squared error criterion. The squared error criterion does not accurately represent the fidelity requirements for scientific image compression. In this paper we propose a distortion measure which correlates with subjective evaluations, and an adaptive vector quantization algorithm which minimizes this distortion measure. A new approach to codebook design is presented to replace the nearest neighbor approach.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1247-1250 |
| Number of pages | 4 |
| Journal | Conference Record of the Asilomar Conference on Signals, Systems and Computers |
| Volume | 2 |
| State | Published - 1998 |
| Event | Proceedings of the 1998 32nd Asilomar Conference on Signals, Systems & Computers. Part 1 (of 2) - Pacific Grove, CA, USA Duration: Nov 1 1998 → Nov 4 1998 |
ASJC Scopus subject areas
- Signal Processing
- Computer Networks and Communications