A New Sense for Depth of Field
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fronts propagating with curvature-dependent speed: algorithms based on Hamilton-Jacobi formulations
Journal of Computational Physics
Depth from focus using pyramid architecture
Pattern Recognition Letters
An Investigation of Methods for Determining Depth from Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
Depth from defocus: a spatial domain approach
International Journal of Computer Vision
A variational level set approach to multiphase motion
Journal of Computational Physics
A simple level set method for solving Stefan problems
Journal of Computational Physics
A Variational Approach to Recovering Depth From Defocused Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
International Journal of Computer Vision
Rational Filters for Passive Depth from Defocus
International Journal of Computer Vision
Optimization by Vector Space Methods
Optimization by Vector Space Methods
IEEE Transactions on Pattern Analysis and Machine Intelligence
Shape and Radiance Estimation from the Information-Divergence of Blurred Images
ECCV '00 Proceedings of the 6th European Conference on Computer Vision-Part I
On Observing Shape from Defocused Images
ICIAP '99 Proceedings of the 10th International Conference on Image Analysis and Processing
The Optimal Axial Interval in Estimating Depth from Defocus
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Passive Depth From Defocus Using a Spatial Domain Approach
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part II
Projection defocus analysis for scene capture and image display
ACM SIGGRAPH 2006 Papers
International Journal of Computer Vision
Real Aperture Axial Stereo: Solving for Correspondences in Blur
Proceedings of the 31st DAGM Symposium on Pattern Recognition
Restoration of images with piecewise space-variant blur
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
3D shape from anisotropic diffusion
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
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We address the problem of estimating the three-dimensional shape and radiance of a surface in space from images obtained with different focal settings. We pose the problem as an infinite-dimensional optimization and seek for the global shape of the surface by numerically solving a partial differential equation (PDE). Our method has the advantage of being global (so that regularization can be imposed explicitly), efficient (we use level set methods to solve the PDE), and geometrically correct (we do not assume a shift-invariant imaging model, and therefore are not restricted to equifocal surfaces).