Paper
1 April 1998 Lossless compression of prepress images using a novel color decorrelation technique
Steven Van Assche, Wilfried R. Philips, Ignace L. Lemahieu
Author Affiliations +
Proceedings Volume 3308, Very High Resolution and Quality Imaging III; (1998) https://doi.org/10.1117/12.302430
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
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 listless compression is acceptable. Most existing listless 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 a new listless color transform is proposed, based on the Karhunen- Loeve Transform (KLT). This transform removes redundancies in the color representation of each pixel and can be combined with many existing compression schemes. In this paper it is combined with a prediction scheme that exploits spatial redundancies. The results proposed in this paper show that the color transform effectively decorrelates the color components and that it typically saves about a half to two bit per pixel, compared to a purely predictive scheme.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Steven Van Assche, Wilfried R. Philips, and Ignace L. Lemahieu "Lossless compression of prepress images using a novel color decorrelation technique", Proc. SPIE 3308, Very High Resolution and Quality Imaging III, (1 April 1998); https://doi.org/10.1117/12.302430
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Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

Image compression

Quantization

Data compression

Spatial resolution

Binary data

Image resolution

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