Forward adaptive modeling for context-based compression of large binary images in applications requiring spatial access

A method for compression of 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. Compression stage is performed by JBIG arithmetic coder, namely the QM-coder. The method improves the compression performance significantly in comparison to JBIG if it is used in a similar manner. Only minor modifications to the existing software implementations are required. Implementation details are provided.