论文标题
使用时空相孔码编码的运动去缩合
Motion Deblurring using Spatiotemporal Phase Aperture Coding
论文作者
论文摘要
运动模糊是摄影中的一个已知问题，因为它限制了捕获移动物体的曝光时间。进行了广泛的研究以补偿它。在这项工作中，提出并证明了一种用于运动去膨胀的计算成像方法。在图像采集过程中，使用透镜孔径中的动态相编码，将运动的轨迹编码在中间光学图像中。该编码通过为每个对象的空间模糊着色，从而嵌入了运动方向和范围。颜色提示是使用卷积神经网络（CNN）实施的盲目脱毛过程的先验信息，该卷积神经网络（CNN）训练有素来利用这种编码进行图像恢复。我们证明了所提出的方法比盲人的优势，没有编码和其他使用编码采集的解决方案，无论是在模拟和现实世界实验中。
Motion blur is a known issue in photography, as it limits the exposure time while capturing moving objects. Extensive research has been carried to compensate for it. In this work, a computational imaging approach for motion deblurring is proposed and demonstrated. Using dynamic phase-coding in the lens aperture during the image acquisition, the trajectory of the motion is encoded in an intermediate optical image. This encoding embeds both the motion direction and extent by coloring the spatial blur of each object. The color cues serve as prior information for a blind deblurring process, implemented using a convolutional neural network (CNN) trained to utilize such coding for image restoration. We demonstrate the advantage of the proposed approach over blind-deblurring with no coding and other solutions that use coded acquisition, both in simulation and real-world experiments.
