Forward-adaptive Method for Context-based Compression of Large Binary Images

A method for compressing large binary images is proposed for applications where spatial access to the image is required. The proposed method is a two-stage combination of forward-adaptive modeling and backward-adaptive context based compression with re-initialization of statistics. The method improves compression performance significantly in comparison to a straightforward combination of JBIG and tiling. Only minor modifications to the QM-coder are required and therefore existing software implementations can be easily utilized. Technical details of the modifications are provided.