Shape from focus using optimization technique
2006 IEEE International Conference on Acoustics Speech and Signal …, 2006•ieeexplore.ieee.org
Three dimensional (3D) shape recovery using shape from focus (SFF) is presented as an
optimization problem, ie, maximization of the focus measure in the 3D image volume. The
whole image volume (sequence) is divided into a number of sub image volumes. The search
of 3D shape is made in the sub image volumes using dynamic programming optimization
technique. The final depth map is obtained by collecting the depth map of the sub volumes.
The new algorithm has considerably decreased the computational complexity by searching …
optimization problem, ie, maximization of the focus measure in the 3D image volume. The
whole image volume (sequence) is divided into a number of sub image volumes. The search
of 3D shape is made in the sub image volumes using dynamic programming optimization
technique. The final depth map is obtained by collecting the depth map of the sub volumes.
The new algorithm has considerably decreased the computational complexity by searching …
Three dimensional (3D) shape recovery using shape from focus (SFF) is presented as an optimization problem, i.e., maximization of the focus measure in the 3D image volume. The whole image volume (sequence) is divided into a number of sub image volumes. The search of 3D shape is made in the sub image volumes using dynamic programming optimization technique. The final depth map is obtained by collecting the depth map of the sub volumes. The new algorithm has considerably decreased the computational complexity by searching the 3D shape in sub image volumes and has shown better results. New 3D focus measure operators are also introduced for higher accuracy at the cost of some computational costs.
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