Incremental sampling can be applied in scientific imaging techniques whenever the measurements are taken incrementally, i.e., one pixel position is measured at a time. It can be used to reduce the measurement time as well as the dose impinging onto a specimen. For incremental sampling, the choice of the sampling pattern plays a major role in order to achieve a high reconstruction quality. Besides using static incremental sampling patterns, it is also possible to dynamically adapt the sampling pattern based on the already measured data. This is called dynamic sampling and allows for a higher reconstruction quality, as the inhomogeneity of the sampled image content can be taken into account. Several approaches for dynamic sampling have been published in the literature. However, they share the common drawback that homogeneous regions are sampled too late. This reduces the reconstruction quality as fine details can be missed. We overcome this drawback using a novel probabilistic approach to dynamic image sampling (PADIS). It is based on a data driven probability mass function which uses a local variance map. In our experiments, we evaluate the reconstruction quality for scanning electron microscopy images as well as for natural image content. For scanning electron microscopy images with a sampling density of 35% and frequency selective reconstruction, our approach achieves a PSNR gain of +0.92 dB compared to other dynamic sampling approaches and +1.42 dB compared to the best static patterns. For natural images, even higher gains are achieved. Experiments with additional measurement noise show that for our method the sampling patterns are more stable. Moreover, the runtime is faster than for the other methods.

中文翻译：

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使用基于新方差的概率质量函数的动态图像采样

增量采样可以应用于科学成像技术中，无论何时增量进行测量，即一次测量一个像素位置。它可用于减少测量时间以及影响样本的剂量。对于增量采样，采样模式的选择对于实现高重建质量起着重要作用。除了使用静态增量采样模式外，还可以根据已测量的数据动态调整采样模式。这称为动态采样并允许更高的重建质量，因为可以考虑采样图像内容的不均匀性。文献中已经发表了几种动态采样方法。然而，它们都有一个共同的缺点，即对同质区域采样太晚。这会降低重建质量，因为可能会错过精细的细节。我们使用一种新颖的动态图像采样概率方法 (PADIS) 克服​​了这个缺点。它基于使用局部方差图的数据驱动的概率质量函数。在我们的实验中，我们评估了扫描电子显微镜图像以及自然图像内容的重建质量。对于采样密度为 35% 和频率选择性重建的扫描电子显微镜图像，与其他动态采样方法相比，我们的方法实现了 +0.92 dB 的 PSNR 增益，与最佳静态模式相比实现了 +1.42 dB。对于自然图像，甚至可以获得更高的增益。附加测量噪声的实验表明，对于我们的方法，采样模式更稳定。此外，运行时间比其他方法快。