Defocus deblurring with a coded aperture

Lin Mei, Xuan Cai, Weihao Liu
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引用次数: 3

Abstract

A conventional camera always captures blurred images of scene information away from the focal plane. Deblurring those blurred images is a very important and challenging job in many fields including optics, astronomy, computer vision and computer graphics. Since the defocus kernel plays a key role in the image degradation and the image recovery, many people have bent themselves to the study on the defocus kernel and achieved a lot of results. In this paper, we insert a broadband mask into the aperture of the camera lens to preserve more high frequency information for facilitating the defocus deblurring. We propose a genetic algorithm for computing the defocus kernel of a fixed distance away from the focal plane using a given sharp image and a defocused one. Finally, we implement extensive experiments to show that the computed defocus kernel can produce better images.
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用编码光圈进行散焦去模糊
传统的相机总是在焦平面之外捕捉场景信息的模糊图像。在光学、天文学、计算机视觉和计算机图形学等许多领域,消除这些模糊图像是一项非常重要且具有挑战性的工作。由于离焦核在图像退化和图像恢复中起着关键作用,许多人致力于对离焦核的研究,并取得了许多成果。在本文中,我们在相机镜头的光圈中插入宽带掩模,以保留更多的高频信息,从而促进离焦去模糊。我们提出了一种遗传算法来计算离焦平面固定距离的离焦核,使用给定的清晰图像和离焦图像。最后,我们进行了大量的实验,证明计算的离焦核可以产生更好的图像。
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