Bajaj Chandrajit, Castrillon-Candas Julio, Siddavanahalli Vinay, Xu Zaiqing
Computational Visualization Center, Department of Computer Sciences and, Institute for Computational and Engineering Sciences, ACES 2.128, 24th & Speedway, University of Texas, Austin, Texas 78712, USA.
Structure. 2005 Mar;13(3):463-71. doi: 10.1016/j.str.2005.02.004.
We introduce a new and unified, compressed volumetric representation for macromolecular structures at varying feature resolutions, as well as for many computed associated properties. Important caveats of this compressed representation are fast random data access and decompression operations. Many computational tasks for manipulating large structures, including those requiring interactivity such as real-time visualization, are greatly enhanced by utilizing this compact representation. The compression scheme is obtained by using a custom designed hierarchical wavelet basis construction. Due to the continuity offered by these wavelets, we retain very good accuracy of molecular surfaces, at very high compression ratios, for macromolecular structures at multiple resolutions.
我们引入了一种全新且统一的压缩体积表示法，用于表示不同特征分辨率下的大分子结构以及许多计算得到的相关属性。这种压缩表示法的重要注意事项是快速随机数据访问和解压缩操作。利用这种紧凑表示法，许多用于处理大型结构的计算任务，包括那些需要交互性（如实时可视化）的任务，都得到了极大的提升。压缩方案是通过使用定制设计的分层小波基构造获得的。由于这些小波提供的连续性，对于多种分辨率下的大分子结构，我们在非常高的压缩率下仍能保持分子表面的高精度。
