Context based arithmetic coding is the key component of the new JPEG2000 standard. For significance coding

JPEG2000 designs empirically context model using eight adjacent coefficients and classifies all context events into 9 conditional contexts and every bit plane use the same context classification maps. This paper addresses the improvement of significance coding and context modeling for significance coding in the JPEG2000 which enlarges the context template which was 3×3 square region in JPEG2000.We propose a new scan method based on significant context and exploit optimization techniques for context quantization by minimum description length considering the difference of statistic among sub scans.Finally

we establish different context models for different sub scans. Our experimental results show that the lossless compression performance of our scheme is improved 1.312% upon that of JPEG2000.