Accurate Recovery of Three-Dimensional Shape from Image Focus
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robust Regularized Kernel Regression
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Kernel Regression for Image Processing and Reconstruction
IEEE Transactions on Image Processing
A heuristic approach for finding best focused shape
IEEE Transactions on Circuits and Systems for Video Technology
| Hi-index | 0.00 |
In conventional focus measures, focus values are locally aggregated to suppress the noise and to obtain better depth maps. However, this enlarges the difference between focus values of two consecutive frames which results in inaccurate shape. In this paper, we propose a nonparametric approach for 3D shape from image focus by applying an unsupervised formulation of kernel regression estimate. The focus volume is obtained through a focus measure and then Nadaraya and Watson Estimate (NWE) is applied to each frame. The depth is then computed by finding the frame number which maximizes the focus value. The kernel regression is again applied on depth values to obtain an accurate 3D shape. The proposed approach is experimented using synthetic and real image sequences. The results demonstrate the effectiveness of the proposed approach.