Paper
28 December 2001 Rate-distortion-based segmentation for MRC compression
Author Affiliations +
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.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hui Cheng, Guotong Feng, and 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); https://doi.org/10.1117/12.452978
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Cited by 10 scholarly publications.
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KEYWORDS
Image segmentation

Image compression

Image processing algorithms and systems

Distortion

Quantization

Raster graphics

Binary data

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