Evaluation of Pointerless Sparse Voxel Octrees Encoding Schemes Using Huffman Encoding for Dense Volume Datasets Storage

B. Madoš, E. Chovancová, M. Hasin
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引用次数: 3

Abstract

The paper deals with the problematics of the volume datasets representation using pointerless sparse voxel octrees hierarchical data structure. While this data structure, and derived hierarchical data structures based on the use of directed acyclic graphs, are popular in representation of the geometry of the three-dimensional scenes, their efficiency in the representation of other properties of voxels, e.g. color, is lower, due to the lower success in the lossless compression of the data. One of the solutions is to decompose volume dataset that comprises multi-bit values of its voxels, into bit planes and to use classical approach of their encoding to the sparse voxel hierarchical data structures. The paper evaluates this approach along with the different encoding schemes of pointerless sparse voxel octrees in case of multi-bit volume datasets that were obtained by non-invasive medical imaging techniques, including Computed Tomography and Magnetic Resonance Imaging. Five encoding schemes were leveraged in the paper and using test results, their lossless compression capabilities were evaluated.
基于Huffman编码的无指针稀疏体素八叉树编码方案的评价
本文研究了用无指针稀疏体素八叉树分层数据结构表示体数据集的问题。虽然这种数据结构以及基于有向无环图的派生层次数据结构在表示三维场景的几何形状方面很受欢迎,但由于在数据无损压缩方面的成功率较低,它们在表示体素的其他属性(例如颜色)方面的效率较低。其中一种解决方案是将包含其体素的多位值的体数据集分解为位平面,并使用其编码的经典方法对稀疏体素分层数据结构进行编码。本文在非侵入性医学成像技术(包括计算机断层扫描和磁共振成像)获得的多比特体积数据集的情况下,对该方法以及无指针稀疏体素八叉树的不同编码方案进行了评估。本文利用5种编码方案,并结合测试结果,对其无损压缩能力进行了评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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