Affiliation:
1. Future Convergence Engineering, School of Computer Science and Engineering, Korea University of Technology and Education, 1600 Chungjeolro, Byeongcheonmyeon, Cheonan 31253, Republic of Korea
Abstract
In the shape-from-focus (SFF) method, the quality of the 3D shape generated relies heavily on the focus measure operator (FM) used. Unfortunately, most FMs are sensitive to noise and provide inaccurate depth maps. Among recent FMs, the ring difference filter (RDF) has demonstrated excellent robustness against noise and reasonable performance in computing accurate depth maps. However, it also suffers from the response cancellation problem (RCP) encountered in multidimensional kernel-based FMs. To address this issue, we propose an effective and robust FM called the directional ring difference filter (DRDF). In DRDF, the focus quality is computed by aggregating responses of RDF from multiple kernels in different directions. We conducted experiments using synthetic and real image datasets and found that the proposed DRDF method outperforms traditional FMs in terms of noise handling and producing a higher quality 3D shape estimate of the object.
Funder
National Research Foundation of Korea
Subject
General Mathematics,Engineering (miscellaneous),Computer Science (miscellaneous)