Reliability measure for shape-from-focus

  • Authors:

  • Said Pertuz;Domenec Puig;Miguel Angel Garcia

  • Affiliations:

  • Intelligent Robotics and Computer Vision Group, Department of Computer Science and Mathematics, Universitat Rovira i Virgili, Spain;Intelligent Robotics and Computer Vision Group, Department of Computer Science and Mathematics, Universitat Rovira i Virgili, Spain;Department of Electronic and Communications Technology, Autonomous University of Madrid, Spain

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2013

Quantified Score

Hi-index 0.00

Visualization

Abstract

Shape-from-focus (SFF) is a passive technique widely used in image processing for obtaining depth-maps. This technique is attractive since it only requires a single monocular camera with focus control, thus avoiding correspondence problems typically found in stereo, as well as more expensive capturing devices. However, one of its main drawbacks is its poor performance when the change in the focus level is difficult to detect. Most research in SFF has focused on improving the accuracy of the depth estimation. Less attention has been paid to the problem of providing quality measures in order to predict the performance of SFF without prior knowledge of the recovered scene. This paper proposes a reliability measure aimed at assessing the quality of the depth-map obtained using SFF. The proposed reliability measure (the R-measure) analyzes the shape of the focus measure function and estimates the likelihood of obtaining an accurate depth estimation without any previous knowledge of the recovered scene. The proposed R-measure is then applied for determining the image regions where SFF will not perform correctly in order to discard them. Experiments with both synthetic and real scenes are presented.