Separation of Transparent Layers using Focus
International Journal of Computer Vision
Depth from Defocus vs. Stereo: How Different Really Are They?
International Journal of Computer Vision - Special issue on computer vision research at the Technion
A Variational Approach to Shape from Defocus
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Shape and Radiance Estimation from the Information-Divergence of Blurred Images
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
A Geometric Approach to Shape from Defocus
IEEE Transactions on Pattern Analysis and Machine Intelligence
ACM SIGGRAPH 2006 Papers
On defocus, diffusion and depth estimation
Pattern Recognition Letters
Virtual focus and depth estimation from defocused video sequences
IEEE Transactions on Image Processing
Coded Aperture Pairs for Depth from Defocus and Defocus Deblurring
International Journal of Computer Vision
Optimized aperture shapes for depth estimation
Pattern Recognition Letters
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We analyze the effect of perturbations on the estimation of Depth from Defocus (DFD) implemented by changing the focus setting (e.g., axially moving the sensor). The analysis yields the optimal change of focus setting, and the spatial frequencies for which estimation is most robust. For stable estimation at all spatial frequencies, the change in focus setting should be less than twice the depth of field. For the most robust estimation in the highest spatial frequencies the axial interval should be equal to the depth of field.