Paper
2 January 1998 Fast autocorrelation-based context template selection scheme for lossless compression of halftone images
Koen N.A. Denecker, Steven Van Assche, Ignace L. Lemahieu
Author Affiliations +
Abstract
Recently, new applications such as printing on demand and personalized printing have arisen where lossless halftone image compression can be useful for increasing transmission speed and lowering storage costs. State-of-the-art lossless bilevel image compression schemes like JBIG only achieve moderate compression ratios due to the periodic dot structure of classical halftones. In this paper, we present two improvements on the context modeling scheme. Firstly, we adapt the context template to the periodic structure of the halftone image. This is a non-trivial problem for which we propose a fast close-to-optimal context selection scheme based on the calculation and sorting of the autocorrelation function on a part of the image. Secondly, increasing the order of the model produces an additional gain in compression. We have experimented with classical halftones of different resolutions and sizes, screened under different angles, and produced by either a digital halftoning algorithm or a digital scanner. The additional coding time for context selection is negligible, while the decoding time remains the same. The global improvement with respect to JBIG (which has features like one adaptive pixel, histogram rescaling and multiresolution decomposition) is about 30% to 65%, depending on the image.
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Koen N.A. Denecker, Steven Van Assche, and Ignace L. Lemahieu "Fast autocorrelation-based context template selection scheme for lossless compression of halftone images", Proc. SPIE 3300, Color Imaging: Device-Independent Color, Color Hardcopy, and Graphic Arts III, (2 January 1998); https://doi.org/10.1117/12.298288
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Cited by 4 scholarly publications.
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KEYWORDS
Halftones

Image compression

Printing

Ions

Statistical analysis

Image quality standards

Statistical modeling

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