JBIG

JBIG is a lossless image compression standard from the Joint Bi-level Image Experts Group, standardized as ISO/IEC standard 11544 and as ITU-T recommendation T.82. It is widely implemented in fax machines. Now that the newer bi-level image compression standard JBIG2 has been released, JBIG is also known as JBIG1. JBIG was designed for compression of binary images, particularly for faxes, but can also be used on other images. In most situations JBIG offers between a 20% and 50% increase in compression efficiency over the Fax Group 4 standard, and in some situations, it offers a 30-fold improvement.

JBIG is based on a form of arithmetic coding developed by IBM (known as the Q-coder) that also uses a relatively minor refinement developed by Mitsubishi, resulting in what became known as the QM-coder. It bases the probability estimates for each encoded bit on the values of the previous bits and the values in previous lines of the picture. JBIG also supports progressive transmission, which generally incurs a small overhead in bit rate (around 5%).

JBIG2

JBIG2 is an image compression standard for bi-level images, developed by the Joint Bi-level Image Experts Group. It is suitable for both lossless and lossy compression. According to a press release from the Group, in its lossless mode JBIG2 typically generates files one third to one fifth the size of Fax Group 4 and one half to one quarter the size of JBIG, the previous bi-level compression standard released by the Group. JBIG2 has been published in 2000 as the international standard ITU T.88, and in 2001 as ISO/IEC 14492.

Functionality

Ideally, a JBIG2 encoder will segment the input page into regions of text, regions of halftone images, and regions of other data. Regions which are neither text nor halftones are typically compressed using a context-dependent arithmetic coding algorithm called the QM coder. Textual regions are compressed as follows: the foreground pixels in the regions are grouped into symbols. A dictionary of symbols is then created and encoded, typically also using context-dependent arithmetic coding, and the regions are encoded by describing which symbols appear where. Typically, a symbol will correspond to a character of text, but this is not required by the compression method. For lossy compression the difference between similar symbols (e.g., slightly different impressions of the same letter) can be neglected; for lossless compression, this difference is taken into account by compressing one similar symbol using another as a template. Halftone images may be compressed by reconstructing the grayscale image used to generate the halftone and then sending this image together with a dictionary of halftone patterns. Overall, the algorithm used by JBIG2 to compress text is very similar to the JB2 compression scheme used in the DjVu file format for coding binary images.