A Novel Technique of Image-Based Camera Calibration in Depth-from-Defocus

Quanbing Zhang, Y. Gong
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引用次数: 2

Abstract

In this paper, a novel camera parameters calibration algorithm is proposed by exploiting defocus information. The proposed algorithm is based on two defocus images of the same scene obtained by changing camera's aperture numbers. Both images can be arbitrarily blurred. The blur difference between the two defocused images was estimated. Combining with imaging geometry of the thin lens, the corresponding camera parameters can be calibrated. This proposed algorithm remove the limit of calibration algorithm given by Soon-Yong Park that one of the images used in calibration must be focused. And it is valid without process of scale normalization. The calibrated parameters yield consistent results in depth estimation. Experimental results on synthetic and real images are presented to demonstrate the effectiveness of the proposed algorithm.
基于图像的相机离焦深度标定新技术
本文提出了一种利用离焦信息标定相机参数的新算法。该算法基于通过改变相机光圈数获得的同一场景的两幅离焦图像。这两幅图像都可以任意模糊。估计了两幅散焦图像的模糊差值。结合薄透镜的成像几何形状,可以对相应的相机参数进行标定。该算法消除了Park Soon-Yong给出的标定算法必须将其中一幅图像聚焦的限制。该方法不需要尺度归一化处理,是有效的。校正后的参数在深度估计中得到一致的结果。在合成图像和真实图像上的实验结果验证了该算法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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