Abstract Compressed ultrafast photography (CUP), as the fastest receive-only ultrafast imaging technology by combining steak imaging and compressed sensing (CS), has shown to be a powerful tool to measure ultrafast dynamic scenes. Through a reconstruction algorithm based on CS, CUP can capture the three-dimensional image information of non-repetitive transient events with a single exposure. However, it still suffers from poor image reconstruction quality on account of the super-high data compression ratio induced by the undersampling strategy. Here, we propose a total variation (TV) combined with block matching and 3D filtering (BM3D) reconstruction algorithm to improve the image quality of CUP, which is named as the TV-BM3D algorithm. The proposed algorithm can simultaneously exploit gradient sparsity and non-local similarity for image reconstruction by incorporating TV and BM3D denoisers. Both the numerical simulations and experimental results show that, compared with the two conventional two-step iterative shrinkage/thresholding and augmented Lagrangian algorithms in CUP, the TV-BM3D algorithm can not only improve the image reconstruction quality, but also strengthen the noise immunity of this technique. It is prospected that these improvements in image reconstruction will further promote the practical applications of CUP in capturing complex physical and biological dynamics.

中文翻译：

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用于单次压缩超快摄影的全变分和块匹配基于 3D 滤波的图像重建

摘要 压缩超快摄影（CUP）作为最快的仅接收超快成像技术，结合牛排成像和压缩传感（CS），已被证明是测量超快动态场景的强大工具。通过基于 CS 的重建算法，CUP 可以通过单次曝光捕获非重复瞬态事件的三维图像信息。然而，由于欠采样策略引起的超高数据压缩比，它仍然存在图像重建质量差的问题。在这里，我们提出了一种结合块匹配和 3D 滤波 (BM3D) 重建算法的全变分 (TV) 来提高 CUP 的图像质量，称为 TV-BM3D 算法。所提出的算法可以通过结合 TV 和 BM3D 降噪器同时利用梯度稀疏性和非局部相似性进行图像重建。数值模拟和实验结果均表明，与CUP中两种常规的两步迭代收缩/阈值和增广拉格朗日算法相比，TV-BM3D算法不仅可以提高图像重建质量，而且增强了对噪声的抗扰度。这种技术。预计这些图像重建方面的改进将进一步推动 CUP 在捕捉复杂的物理和生物动力学方面的实际应用。与CUP中两种传统的两步迭代收缩/阈值和增广拉格朗日算法相比，TV-BM3D算法不仅可以提高图像重建质量，还可以增强该技术的抗噪能力。预计这些图像重建方面的改进将进一步推动 CUP 在捕捉复杂的物理和生物动力学方面的实际应用。与CUP中两种传统的两步迭代收缩/阈值和增广拉格朗日算法相比，TV-BM3D算法不仅可以提高图像重建质量，还可以增强该技术的抗噪能力。预计这些图像重建方面的改进将进一步推动 CUP 在捕捉复杂的物理和生物动力学方面的实际应用。