title: Absolute depth estimation from a single defocused image.
abstract: Shape from defocus (SFD) is one of the most popular techniques in monocular 3D vision. While most SFD approaches require two or more images of the same scene captured at a fixed view point, this paper presents an efficient approach to estimate absolute depth from a single defocused image. Instead of directly measuring defocus level of each pixel, we propose to design a sequence of aperture-shape filters to segment a defocused image by defocus level. A boundary-weighted belief propagation algorithm is employed to obtain a smooth depth map. We also give an estimation of depth error. Extensive experiments show that our approach outperforms the state-of-the-art single-image SFD approaches both in precision of the estimated absolute depth and running time.
authors.forename: Jingyu
authors.initials: J
authors.lastname: Lin
authors.forename: Xiangyang
authors.initials: X
authors.lastname: Ji
authors.forename: Wenli
authors.initials: W
authors.lastname: Xu
authors.forename: Qionghai
authors.initials: Q
authors.lastname: Dai
mesh_terms: D000465:Algorithms; D016477:Artifacts; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity