Sample Efficient Fourier Ptychography for Structured Data
Sample Efficient Fourier Ptychography for Structured Data
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DOI：
10.1109/tci.2019.2948758
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发表时间：
2020
影响因子：
5.4
通讯作者：
Gauri Jagatap;Zhengyu Chen;Seyedehsara Nayer;C. Hegde;Namrata Vaswani
中科院分区：
文献类型：
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作者：
Gauri Jagatap;Zhengyu Chen;Seyedehsara Nayer;C. Hegde;Namrata Vaswani
我们研究从傅里叶叠层描记术测量中恢复结构化数据的问题。傅里叶叠层成像是一种图像采集方案，它使用图像阵列在显微镜和长距离成像中产生高分辨率图像，以减轻衍射模糊的影响。测量的数量通常远大于要重建的信号（图像或视频）的大小，这意味着较高的存储和计算要求。利用图像（或视频）的结构特性可以缓解样本复杂度高的问题。在本文中，我们首先讨论一系列子采样方案，这些方案可以减少傅里叶叠层摄影设置中的测量量；然而，这使得问题不适定。相应地，我们对要恢复的信号施加结构约束，以规范问题。通过我们新颖的恢复算法框架，我们表明可以通过对图像（或视频）结构的简单而自然的假设，从更少的样本中重建高分辨率图像（或视频）。我们通过一系列模拟和真实数据的实验证明了我们的主张的有效性。
We study the problem of recovering structured data from Fourier ptychography measurements. Fourier ptychography is an image acquisition scheme that uses an array of images to produce high-resolution images in microscopy as well as long-distance imaging, to mitigate the effects of diffraction blurring. The number of measurements is typically much larger than the size of the signal (image or video) to be reconstructed, which translates to high storage and computational requirements. The issue of high sample complexity can be alleviated by utilizing structural properties of the image (or video). In this article, we first discuss a range of sub-sampling schemes which can reduce the amount of measurements in Fourier ptychography setups; however, this makes the problem ill-posed. Correspondingly, we impose structural constraints on the signals to be recovered, to regularize the problem. Through our novel framework of recovery algorithms, we show that one can reconstruct high-resolution images (or video) from fewer samples, via simple and natural assumptions on the structure of the images (or video). We demonstrate the validity of our claims through a series of experiments, both on simulated and real data.