用于科学可视化的小波介绍

Georges-Pierre Bonneau
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引用次数: 2

摘要

本文介绍了小波技术在科学可视化中的应用。小波是表示大型复杂数据集的强大工具。对可以用小波表示的数据集的类型有一些限制。这些限制将在第一部分中描述。然后,解释了小波表示的基本概念:细节层次空间、小波空间、分解和重构算法。小波的正交性及其与计算最佳逼近能力的关系是下一部分的主题。然后回顾了小波表示在科学可视化中的常用应用。这些包括渐进式传输,LOD可视化,局部区域缩放。最后一部分致力于小波技术的最新推广,该技术处理由于第一部分中描述的限制而无法用常规小波表示处理的某些类型的数据集。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Introduction to Wavelets for Scientific Visualization
This paper gives an introduction to wavelet techniques in the context of Scientific Visualization. Wavelets are a powerful tool for the representation of large and complex data sets. Some restrictions apply on the type of data sets which can be represented by wavelets. These restrictions are described in a first part. Thereafter, the basic concepts of wavelet representations are explained: level of detail spaces, wavelet spaces, decomposition and reconstruction algorithms. Orthogonality properties of wavelets and their relations with the ability of computing best approximations are the subject of the next part. Usual applications of wavelet representations in Scientific Visualization are then reviewed. These include progressive transmission, LOD visualization, local area zooming. The last part is dedicated to a recent generalization of wavelet techniques that deals with some types of data sets that cannot be tackle by usual wavelet representations due to the restrictions described in the first part.
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