Abstract
An efficient compression scheme for color-quantized images based on progressive coding of color information has been developed. Instead of sorting color indexes into a linear list structure, a binary-tree structure of color indexes is proposed. With this structure, the new algorithm can progressively recover an image from two colors to all of the colors contained in the original image, i.e., a lossless recovery is achieved. Experimental results showed that it can efficiently compress images in both lossy and lossless cases. Typically for color-quantized Lena image with 256 colors, the algorithm achieved 0.5 bpp below state-of-the-art lossless compression methods while preserving the efficient lossy compression. Such a compression scheme is very attractive to many applications that require the ability of fast browsing or progressive transmission, and if necessary, to exactly recover the original image.
| Original language | English |
|---|---|
| Pages (from-to) | 904-908 |
| Journal | IEEE Transactions on Circuits and Systems for Video Technology |
| Volume | 12 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - Oct 2002 |
| Externally published | Yes |
Funding
This work was supported by NKBRSF G1998030606 and by City University under Grant 7001181. This paper was presented in part at the IEEE Conference on Image Processing, Thessaloniki, Greece, October 2002.
Keywords
- Color-quantized images
- Data compression
- Index sorting
- Progressive refinement