28 December 2001 Rate-distortion-based segmentation for MRC compression
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Proceedings Volume 4663, Color Imaging: Device-Independent Color, Color Hardcopy, and Applications VII; (2001); doi: 10.1117/12.452978
Event: Electronic Imaging, 2002, San Jose, California, United States
Abstract
Effective document compression algorithms require scanned document images be first segmented into regions such as text, pictures and background. In this paper, we present a document compression algorithm that is based on the 3-layer (foreground/mask/background)MRC (mixture raster content) model. This compression algorithm first segments a scanned document image into different classes. Then, each class is transformed to the 3-layer MRC model differently according to the property of that class. Finally, the foreground and the back-ground layers are compressed using JPEG with customized quantization tables. The mask layer is compressed using JBIG2. The segmentation is optimized in the sense of rate distortion for the 3-layer MRC representation. It works in a closed loop fashion by a lying each transformation to each region of the document and then selecting the method that yields the best rate-distortion trade-off. The proposed segmentation algorithm can not only achieve a better rate-distortion trade-off, but also produce more robust segmentations by eliminating those mis-classifications which can cause severe artifacts. At similar bit rates, our MRC compression with the rate- distortion based segmentation can achieve a much higher subjective quality than state-of-the-art compression algorithms, such as JPEG and JPEG-2000.
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Hui Cheng, Guotong Feng, Charles A. Bouman, "Rate-distortion-based segmentation for MRC compression", Proc. SPIE 4663, Color Imaging: Device-Independent Color, Color Hardcopy, and Applications VII, (28 December 2001); doi: 10.1117/12.452978; https://doi.org/10.1117/12.452978
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KEYWORDS
Image segmentation

Image compression

Image processing algorithms and systems

Distortion

Quantization

Raster graphics

Binary data

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