摘要
针对基于链表实现的感兴趣区域编码算法占用存储资源较多的问题,提出了一种无链表的编码算法.在SPIHT(等级树集合分裂)编码过程中,采用标志位图表示系数和集合的重要性信息;优先编码感兴趣区域,利用队列缓存非感兴趣区域系数和集合信息;编码非感兴趣区域时,从队列中恢复编码所需的重要性信息.编码过程不需要提升感兴趣区域小波系数,能实现感兴趣区域重建质量的精确控制.仿真实验表明,该算法优于提升小波系数的感兴趣区域编码算法;当编码码率为1 bpp(比特/像素)时,其存储需求仅为链表实现的感兴趣区域分离编码算法的1/10.
To reduce memory requirement of the ROI （ region of interest） coding algorithm based on lists, a new ROI coding algorithm based on listless zero-tree was proposed. In the process of SPIHT （set partitioning in hierarchical trees ）, signed bit planes are used to record the significance information of coefficients and sets. The ROI is encoded first, and the significance information of NROI （non-region of interest ） is recorded in queues, so that the NROI can be encoded with restored significance information from the queues. The simulation results show that the proposed algorithm can get better reconstructed quality than the coding algorithm based on scaling ROI coefficients. It can achieve accurate ROI coding without sealing up ROI coefficients, and needs only one-tenth of memory required by the ROI separate coding algorithm based on lists when the coding rate is 1 bpp （bits/ pixel）.
出处
《西南交通大学学报》
EI
CSCD
北大核心
2010年第1期82-87,共6页
Journal of Southwest Jiaotong University
基金
国家863计划资助项目(2006AA01Z216)
中国科学院方向性创新重大项目(KGCY-SYW-407-02)
关键词
图像压缩
感兴趣区域
等级树集合分裂
无链表零树编码
image compress
region of interest
SPIHT （set partitioning in hierarchical trees）
listless zero-tree coding
