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Enhancing Focus Measurements in Shape From Focus Through 3D Weighted Least Square  

Mahmood, Muhammad Tariq (Korea University of Technology and Education, School of Computer Science and Engineering)
Ali, Usman (Korea University of Technology and Education, School of Computer Science and Engineering)
Choi, Young Kyu (Korea University of Technology and Education, School of Computer Science and Engineering)
Publication Information
Journal of the Semiconductor & Display Technology / v.18, no.3, 2019 , pp. 66-71 More about this Journal
Abstract
In shape from focus (SFF) methods, the quality of image focus volume plays a vital role in the quality of 3D shape reconstruction. Traditionally, a linear 2D filter is applied to each slice of the image focus volume to rectify the noisy focus measurements. However, this approach is problematic because it also modifies the accurate focus measurements that should ideally remain intact. Therefore, in this paper, we propose to enhance the focus volume adaptively by applying 3-dimensional weighted least squares (3D-WLS) based regularization. We estimate regularization weights from the guidance volume extracted from the image sequences. To solve 3D-WLS optimization problem efficiently, we apply a technique to solve a series of 1D linear sub-problems. Experiments conducted on synthetic and real image sequences demonstrate that the proposed method effectively enhances the image focus volume, ultimately improving the quality of reconstructed shape.
Keywords
Shape From Focus (SFF); Focus Measure; Focus Volume Regularization; 3D Weighted Least Squares (3D-WLS);
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Times Cited By KSCI : 2  (Citation Analysis)
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