有损小波重构的空间/误差权衡

John C. Frain, R. Bergeron
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引用次数: 0

摘要

离散小波变换已被证明是一种非常有效的压缩大型数据集的工具。以前的研究是基于给定的空间约束来选择小波系数的子集。这些方法需要不可忽略的开销来维护与保留系数相关的位置信息。我们的方法识别了整个小波系数子带,这些子带可以基于最小化引入重建的总误差来消除。我们可以通过将部分或全部保存的系数编码为字节索引到浮点查找表中来进一步减少空间(同时增加错误)。我们演示了我们的方法如何使用比传统MR实现更少的空间产生相同的全局和误差。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Space/error tradeoffs for lossy wavelet reconstruction
Discrete Wavelet Transforms have proven to be a very effective tool for compressing large data sets. Previous research has sought to select a subset of wavelet coefficients based on a given space constraint. These approaches require non-negligible overhead to maintain location information associated with the retained coefficients. Our approach identifies entire wavelet coefficient subbands that can be eliminated based on minimizing the total error introduced into the reconstruction. We can get further space reduction (with more error) by encoding some or all of the saved coefficients as a byte index into a floating point lookup table. We demonstrate how our approach can yield the same global sum error using less space than traditional MR implementations.
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