Document image compression by nonlinear binary subband decomposition and concatenated arithmetic coding

This paper proposes a new subband coding approach to compression of document images, which is based on nonlinear binary subband decomposition followed by the concatenated arithmetic coding. We choose to use the sampling-exclusive on (XOR) subband decomposition to exploit its beneficial characteristics to conserve the alphabet size of symbols and provide a small region of support while providing the perfect reconstruction property. We propose a concatenated arithmetic coding scheme to alleviate the degradation of predictability caused by subband decomposition, where three high-pass subband coefficients at the same location are concatenated and then encoded by an octave arithmetic coder. The proposed concatenated arithmetic coding is performed based on a conditioning context properly selected by exploiting a nature of the sampling-XOR subband filter bank as well as taking the advantage of noncausal prediction capability of subband coding. We also introduce a unicolor map to efficiently represent large uniform regions frequently appearing in document images. Simulation results show that each of the functional blocks proposed in the paper performs very well, and consequently, the proposed subband coder provides good compression of document images.