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An image-based calibration technique of spatial domain depth-from-defocus

机译:基于图像的空间域离焦深度校正技术

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Depth-from-defocus (DFD) is useful in 3-D range image acquisition and automatic focusing. However, DFD needs precise calibration of internal camera parameters. Most DFD techniques use well known camera calibration techniques or specially designed vision systems to precisely measure the settings of the lens system of a camera. In this paper, we introduce an image-based defocus calibration technique. Especially we employ the Spatial domain Convolution/Deconvolution Transform Method (STM) which is introduced by Sub-barao and Surya [Subbarao, M., Surya, G., 1994. Depth-from-defocus: A spatial domain approach. Internat. J. Comput. Vision 13 (3), 271-294]. STM estimates blur parameters σ_1 and σ_2 of defocused images obtained at two different lens steps of the camera. In STM, the blur difference between two defocused images is considered to be a constant value which is determined by internal camera parameters. We use the blur level of the defocused images to calibrate blur difference and camera parameters. Calibrated parameters yield consistent results in depth estimation. Experimental results of depth measurement using real objects are presented.
机译:离焦深度(DFD)在3-D范围图像采集和自动聚焦中很有用。但是,DFD需要对内部摄像机参数进行精确校准。大多数DFD技术使用众所周知的相机校准技术或专门设计的视觉系统来精确测量相机镜头系统的设置。在本文中,我们介绍了一种基于图像的散焦校准技术。特别是,我们采用了由Sub-barao和Surya [Subbarao,M.,Surya,G.,1994. Depth-from-defocus:空间域方法引入的空间域卷积/解卷积变换方法(STM)。国际交流。 J.计算机Vision 13(3),271-294]。 STM估计在相机的两个不同镜头步距处获得的散焦图像的模糊参数σ_1和σ_2。在STM中,两个散焦图像之间的模糊差被认为是由内部相机参数确定的恒定值。我们使用散焦图像的模糊度来校准模糊差和相机参数。校准的参数在深度估计中产生一致的结果。提出了使用真实物体进行深度测量的实验结果。

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