| Efficient Hierarchical Structure of Wavelet-Based Compression for Large Volume Data Sets |
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| 作者姓名： | 柯永振 张加万 孙济洲 李佳明 |
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| 作者单位： | School of Computer Science and Technology Tianjin University，School of Computer Science and Technology，Tianjin University，School of Computer Science and Technology，Tianjin University，School of Computer Science and Technology，Tianjin University，Tianjin 300072 China，School of Computer Technology and Automation Tianjin Polytechnic University Tianjin 300160 China Tianjin 300072 China Tianjin 300072 China Tianjin 300072 China |
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| 基金项目： | Supported by Natural Science Foundation of China (No. 60373061). |
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| 摘 要： | With the increasing resolution of medical CTscanners, datasets of 10—100 gigabyte sizes are get-ting more and more common1]. Due to their large si-zes, the transmission between data server and brows-ing clients over low-bandwidth networks and the dis-play of these data sets are time-consuming. There-fore, multiresolution models are developed, so thatthe data can be visualized incrementally as they arrive(progressive refinement). Wavelets are a natural can-didate for such a multiresolution a…
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| 关 键 词： | 微波 压缩 海量数据 随机存取 八叉树 |
| 收稿时间： | 2006-05-23 |
Efficient Hierarchical Structure of Wavelet-Based Compression for Large Volume Data Sets |
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| KE Yongzhen,ZHANG Jiawan,SUN Jizhou,LI Jiaming.Efficient Hierarchical Structure of Wavelet-Based Compression for Large Volume Data Sets[J].Transactions of Tianjin University,2006,12(5):378-382. |
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| Authors: | KE Yongzhen ZHANG Jiawan SUN Jizhou LI Jiaming |
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| Abstract: | With volume size increasing, it is necessary to develop a highly efficient compression algorithm, which is suitable for progressive refinement between the data server and the browsing client. For three-dimensional large volume data, an efficient hierarchical algorithm based on wavelet compression was presented, using intra-band dependencies of wavelet coefficients. Firstly, after applying blockwise hierarchical wavelet decomposition to large volume data, the block significance map was obtained by using one bit to indicate significance or insignificance of the block. Secondly, the coefficient block was further subdivided into eight sub-blocks if any significant coefficient existed in it, and the process was repeated, resulting in an incomplete octree. One bit was used to indicate significance or insignificance, and only significant coefficients were stored in the data stream. Finally, the significant coefficients were quantified and compressed by arithmetic coding. The experimental results show that the proposed algorithm achieves good compression ratios and is suited for random access of data blocks. The results also show that the proposed algorithm can be applied to progressive transmission of 3D volume data. |
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| Keywords: | wavelet compression large volume data fast random access octree |
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