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Optimal selection of camera parameters for recovery of depth from defocused images

机译:最佳选择相机参数以从散焦图像中恢复深度

摘要

In the depth from defocus (DFD) method two defocused images of a scene are obtained by capturing the scene with different sets of camera parameters. An arbitrary selection of the camera settings can result in observed images whose relative blurring is insufficient to yield a good estimate of the depth. In this paper, we study the effect of the degree of relative blurring on the accuracy of the estimate of the depth by addressing the DFD problem in a maximum likelihood-based framework. We propose a criterion for optimal selection of camera parameters to obtain an improved estimate of the depth. The optimality criterion is based on the Cramer-Rao bound of the variance of the error in the estimate of blur. Simulations as well as experimental results on real images are presented for validation.
机译:在离焦深度(DFD)方法中,通过使用不同组的摄影机参数捕获场景来获取场景的两个散焦图像。摄像机设置的任意选择可能会导致观察到的图像的相对模糊度不足以产生良好的深度估计。在本文中,我们通过在基于最大似然的框架中解决DFD问题,研究了相对模糊度对深度估计精度的影响。我们提出了最佳选择相机参数的标准,以获得对深度的改进估计。最佳标准基于模糊估计中误差方差的Cramer-Rao边界。真实图像上的仿真和实验结果均经过验证。

著录项

  • 作者

    RAJAGOPALAN AN; CHAUDHURI S;

  • 作者单位
  • 年度 1997
  • 总页数
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类

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