Title
Computational approach for depth from defocus
Abstract
Active depth from defocus (DFD) eliminates the main limitation faced by passive DFD, namely its inability to recover depth when dealing with scenes defined by weakly textured (or textureless) objects. This is achieved by projecting a dense illumination pattern onto the scene and depth can be recovered by measuring the local blurring of the projected pattern. Since the illumination pattern forces a strong dominant texture on imaged surfaces, the level of blurring is determined by applying a local operator (tuned on the frequency derived from the illumination pattern) as opposed to the case of window-based passive DFD where a large range of band pass operators are required. The choice of the local operator is a key issue in achieving precise and dense depth estimation. Consequently, in this paper we introduce a new focus operator and we propose refinements to compensate for the problems associated with a suboptimal local operator and a nonoptimized illumination pattern. The developed range sensor has been tested on real images and the results demonstrate that the performance of our range sensor compares well with those achieved by other implementations, where precise and computationally expensive optimization techniques are employed. (c) 2005 SPIE and IS&T.
Year
DOI
Venue
2005
10.1117/1.1900743
JOURNAL OF ELECTRONIC IMAGING
Keywords
Field
DocType
vision,lenses,image processing,sensors
Computer vision,Local operator,Band-pass filter,Computer science,Lens (optics),Artificial intelligence,Operator (computer programming),Depth from defocus,Real image
Journal
Volume
Issue
ISSN
14
2
1017-9909
Citations 
PageRank 
References 
6
0.81
20
Authors
3
Name
Order
Citations
PageRank
Ovidiu Ghita123418.12
Paul F. Whelan256139.95
John Mallon3977.88