基于SVD图像子空间去噪的高光谱相位成像

Digital Holography and Three-Dimensional Imaging 2019 Pub Date : 2019-05-19 DOI:10.1364/DH.2019.W1B.2

V. Katkovnik, I. Shevkunov, D. Claus, G. Pedrini, K. Egiazarian

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引用次数: 2

摘要

提出了一种改进的高光谱数据去噪算法。该算法基于复域分块匹配三维滤波器、噪声相关矩阵的估计和奇异值分解特征空间的降维。

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Hyperspectral phase imaging with denoising in SVD image subspace

We propose a modified denoising algorithm for hyperspectral data. The algorithm is based on a complex domain block-matching 3D filter, on estimation of the noise correlation matrix and on dimension reduction of the Singular Value Decomposition (SVD) eigenspace.

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来源期刊

Digital Holography and Three-Dimensional Imaging 2019

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