Name
Abstract | ||
|---|---|---|
We present an optimal chain-code-like representation to code contour shapes; in addition, this representation can be easily extended to a scalable form which structures shape data as the base layer followed by two enhancement layers. A lossy coding scheme is also presented for low-bit-rate applications. Compared with the block-based CAE (context-based arithmetic encoding) method in MPEG-4 and DCC (differential chain coding) with an arithmetic coder, our method not only has a higher compression ratio with fewer computation steps, but also can be applied to layered transmission. The scalability achieved by our scheme can be recognized both spatially and quality-wise. Compared with other scalable shape coding methods, our scheme is simple but more efficient than progressive polygon encoding methods. In case of a base layer with distortion Dn=0.02, our scheme saves about 20-30% of the number of bits, that is, we have a smaller size base layer, which is important in layered transmission. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1109/ICIP.2002.1037993 | ICIP (1) |
Keywords | Field | DocType |
compression ratio,binary shape coding,context-based arithmetic encoding,image segmentation,data compression,contour shapes,scalability,test sequences,video coding,binary codes,differential chain coding,lossy coding,arithmetic codes,mpeg-4,chain code,computer science,arithmetic,mpeg 4,layout,shape,encoding,entropy coding | Computer vision,Polygon,Entropy encoding,Range encoding,Computer science,Shape coding,Artificial intelligence,Data compression,MPEG-4,Arithmetic coding,Context-adaptive binary arithmetic coding | Conference |
Volume | ISSN | Citations |
1 | 1522-4880 | 3 |
PageRank | References | Authors |
0.42 | 4 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mei-Chen Yeh | 1 | 708 | 43.91 |
| Yen-Lin Huang | 2 | 156 | 14.23 |
| Jia-Shung Wang | 3 | 209 | 46.34 |