A Significance Coding Algorithm Based on Layer Model
基于层次模型的重要性编码算法

A significance coding algorithm based on layer model is proposed. Without changing the context template of JPEG2000, the proposed scheme uses an explicit layer template to dynamically arrange the scan path of wavelet coefficients. Experimental results show that the proposed scheme provides better autocorrelation outputted bit stream than stripe scanning of JPEG2000 and Hilbert curve scan; and the proposed scheme improves over stripe scanning and Hilbert curve scanning in terms of average bit rates by 1.06% and 0.57%, respectively. Moreover, the proposed scheme achieves an improvement 1.08% over context quantization optimization algorithms based on JPEG2000 in terms of average bit rates.