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Proceedings Paper

Comparison of lossless compression techniques for prepress color images
Author(s): Steven Van Assche; Koen N.A. Denecker; Wilfried R. Philips; Ignace L. Lemahieu
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Paper Abstract

In the pre-press industry color images have both a high spatial and a high color resolution. Such images require a considerable amount of storage space and impose long transmission times. Data compression is desired to reduce these storage and transmission problems. Because of the high quality requirements in the pre-press industry only lossless compression is acceptable. Most existing lossless compression schemes operate on gray-scale images. In this case the color components of color images must be compressed independently. However, higher compression ratios can be achieved by exploiting inter-color redundancies. In this paper we present a comparison of three state-of-the-art lossless compression techniques which exploit such color redundancies: IEP (Inter- color Error Prediction) and a KLT-based technique, which are both linear color decorrelation techniques, and Interframe CALIC, which uses a non-linear approach to color decorrelation. It is shown that these techniques are able to exploit color redundancies and that color decorrelation can be done effectively and efficiently. The linear color decorrelators provide a considerable coding gain (about 2 bpp) on some typical prepress images. The non-linear interframe CALIC predictor does not yield better results, but the full interframe CALIC technique does.

Paper Details

Date Published: 28 December 1998
PDF: 8 pages
Proc. SPIE 3653, Visual Communications and Image Processing '99, (28 December 1998); doi: 10.1117/12.334646
Show Author Affiliations
Steven Van Assche, Univ. of Ghent (Belgium)
Koen N.A. Denecker, Univ. of Ghent (Belgium)
Wilfried R. Philips, Univ. of Ghent (Belgium)
Ignace L. Lemahieu, Univ. of Ghent (Belgium)


Published in SPIE Proceedings Vol. 3653:
Visual Communications and Image Processing '99
Kiyoharu Aizawa; Robert L. Stevenson; Ya-Qin Zhang, Editor(s)

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