Context-based coding of bilevel images enhanced by digital straight line analysis

A new efficient compression scheme for bilevel images containing locally straight edges is presented. This paper is especially focused on lossless (intra) coding of binary shapes for image and video objects, but other images with similar characteristics such as line drawings, layers of digital maps, or segmentation maps are also encoded efficiently. The algorithm is not targeted at document images with text, which can be coded efficiently with dictionary-based techniques as in JBIG2. The scheme is based on a local analysis of the digital straightness of the causal part of the object boundary, which is used in the context definition for arithmetic encoding. Tested on individual images of standard TV resolution binary shapes and the binary layers of a digital map, the proposed algorithm outperforms PWC, JBIG, JBIG2, and MPEG-4 CAE. On the binary shapes, the code lengths are reduced by 21%, 27%, 28%, and 41%, respectively. On the map layers, the reductions are 31%, 34%, 32%, and 64%, respectively. The algorithm is also more efficient on the test material than the state-of-the-art generic bilevel image coder free tree.