Comparison of different facsimile data compression methods for text, graphics and halftone documents

In order to store digital image data in a pel-by-pel representation a huge amount of storage capacity is necessary. For example a DIN A4 page scanned with a resolution of 300 dpi (dots per inch) needs about 1.1 Mbyte storage capacity in binary representation. This paper deals with various methods to compress binary image data. The focus is to discuss their suitability for archiving usual business documents made up of text, graphics and halftone segments. The two-dimensional CCITT group 4 recommendation is compared with an adaptive prediction algorithm and a Classified Pel-Pattern (CLAP) method. For the latter a very efficient systematic code is given. The Classified Pel-Pattern algorithm achieves the best data compression but at the cost of high complexity. Compressing documents scanned with a resolution of 300 dpi the measured compression ratio is between 1.3–2.5 (halftone pictures) and 50 (line art). Considering only text and graphic documents the recommendation of the CCITT is 5–10% worse but complexity is significantly less. However, it is found that this methods show unsatisfactory results applied to halftone pictures.