We present a new approach to coherent averaging in digital holography using singular value decomposition (SVD). Digital holography enables the extraction of phase information from intensity measurements. For this reason, SVD can be used to statistically determine the orthogonal vectors that align the complex-valued measurements from multiple frames and group common modes accounting for constant phase shift terms. The SVD approach enables the separation of multiple signals, which can be applied to remove undesired artifacts such as scatter in retrieved images. The advantages of the SVD approach are demonstrated here in experiments through fog-degraded holograms with spatially incoherent and coherent scatter.

中文翻译：

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数字全息术中相干平均的奇异值分解方法。

我们提出了一种使用奇异值分解（SVD）进行数字全息相干平均的新方法。数字全息术能够从强度测量中提取相位信息。因此，SVD可用于统计确定正交向量，这些正交向量将来自多个帧的复数值测量结果对齐，并考虑了恒定的相移项而对共模进行分组。SVD方法可实现多个信号的分离，可将其应用于去除不想要的伪影，例如在检索到的图像中进行散射。SVD方法的优势在此处通过具有空间不连贯和连贯散射的雾分解全息图在实验中得到了证明。