Name
Abstract | ||
|---|---|---|
A novel approach to still-picture data compression is presented that is based on the integration of two different coding techniques. Its aim is to obtain high-compression factors by exploiting the characteristics of a second-generation method (i.e., polynomial approximation) in suitable scene areas, while achieving higher fidelity, where required by the local image characteristics, through a first-generation technique (i.e., vector quantization). Such a region-driven hybrid approach performs the integration by utilizing a control image (resulting from the detection of areas characterized by high spatial frequencies) that drives the segmentation and approximation processes. The results obtained on a variety of natural color images are quite satisfactory. The visual quality of the reconstructed images is, in general, very good, and SNR is kept within an acceptable range. Moreover, the bit rate obtained is always below 0.15 bit/pixel (bit/pixel), with peak values of 0.07 bit/pixel. |
Year | DOI | Venue |
|---|---|---|
1993 | 10.1002/ett.4460040214 | EUROPEAN TRANSACTIONS ON TELECOMMUNICATIONS |
Keywords | Field | DocType |
data compression | Computer vision,Fidelity,Polynomial,Computer science,Bit rate,Electronic engineering,Coding (social sciences),Vector quantization,Artificial intelligence,Pixel,Data compression,Spatial frequency | Journal |
Volume | Issue | ISSN |
4 | 2 | 1120-3862 |
Citations | PageRank | References |
1 | 0.35 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| De Natale Francesco | 1 | 262 | 40.77 |
| Giuseppe Desoli | 2 | 389 | 41.91 |
| Daniele D. Giusto | 3 | 143 | 31.23 |
| Gianni Vernazza | 4 | 378 | 50.89 |