压缩感知中的量子涨落

Hui Wang, Shensheng Han, M. Kolobov
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摘要

压缩感知(CS)是一种新的信号和图像处理方法,它允许从比奈奎斯特/香农定理所需的小得多的样本中精确恢复图像。压缩感知使用被称为“稀疏性”的对象先验信息,这意味着只有少数图像样本是非零的。考虑到图像中的量子涨落,我们分析了CS的超分辨行为。我们的分析可以描述由光的量子特性所施加的CS的最终能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum fluctuations in Compressed Sensing
Compressed Sensing (CS) is a new method of signal and image processing which allows for exact recovery of an image from a number of samples much smaller than that required by the Nyquist/Shannon theorem. Compressed Sensing uses a priori information about the object called “sparsity”, which means that only a small number of image samples are nonzero. We have analyzed the superresolution behavior of CS taking into account the quantum fluctuations in the image. Our analysis allows to characterize the ultimate capabilities of CS imposed by the quantum nature of the light.
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