Document compression using rate-distortion optimized segmentation

TL;DR: A multilayer compression algorithm for document images that can achieve a much higher subjec- tive quality than state-of-the-art compression algorithms, such as DjVu and SPIHT.

Abstract: Effective document compression algorithms require that scanned document images be first segmented into regions such as text, pictures, and background. In this paper, we present a multilayer compression algorithm for document images. This compression al- gorithm first segments a scanned document image into different classes, then compresses each class using an algorithm specifically designed for that class. Two algorithms are investigated for seg- menting document images: a direct image segmentation algorithm called the trainable sequential MAP (TSMAP) segmentation algo- rithm, and a rate-distortion optimized segmentation (RDOS) algo- rithm. The RDOS algorithm works in a closed loop fashion by apply- ing each coding method to each region of the document and then selecting the method that yields the best rate-distortion trade-off. Compared with the TSMAP algorithm, the RDOS algorithm can of- ten result in a better rate-distortion trade-off, and produce more ro- bust segmentations by eliminating those misclassifications which can cause severe artifacts. At similar bit rates, the multilayer com- pression algorithm using RDOS can achieve a much higher subjec- tive quality than state-of-the-art compression algorithms, such as DjVu and SPIHT. © 2001 SPIE and IS&T. (DOI: 10.1117/1.1344590)