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Snapshot Multiplexed Imaging Based on Compressive Sensing

机译:基于压缩感知的快照多路复用成像

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Multiplexed imaging methods have been proposed to extend the field of view (FoV) of the imaging devices. However, the nature of multiple exposures hinders its application in time-crucial scenarios. In this paper, we design a snapshot multiplexed imaging system for wide FoV imaging. In the system, the scene is first spatially encoded by a mask, and then the coded scene is optically divided into multiple sub-regions which are finally superimposed and measured on a sensor array. We model the demultiplexing as a compressive sensing (CS) reconstruction problem and introduce two methods, one is based on Total Variation (TV) constraint and the other is based on sparsity constraint, to reconstruct the scene. Simulation results demonstrate the effectiveness of the proposed system.
机译:已经提出了多重成像方法以扩展成像装置的视场(FoV)。但是,多次曝光的性质阻碍了它在时间紧迫的场景中的应用。在本文中,我们设计了用于宽FoV成像的快照多路复用成像系统。在该系统中,场景首先通过遮罩在空间上进行编码,然后将编码后的场景从光学上划分为多个子区域,最后将这些子区域叠加并在传感器阵列上进行测量。我们将解复用建模为压缩感知(CS)重建问题,并介绍了两种方法来重建场景,一种方法是基于总变化(TV)约束,另一种是基于稀疏约束。仿真结果证明了该系统的有效性。

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