Depth Recovery by Spectral Energy with Line Spread Functions from a Single Defocused Image
Date Issued
2011
Date
2011
Author(s)
Chen, Cheng-Wei
Abstract
Recovering depth information, distances between objects and the camera, from images is a convenient and practical approach for intelligent 3D technologies. Depth-from-Defocus (DFD), one of the depth recovery methods, utilizes defocus blur to estimate the depth information. The approach has an advantage of using only one single image instead of multiple images to achieve depth recovery. In this thesis, a novel idea to represent the defocus blur amount by the spectral energy of line spread function that is directly derived from defocused step edge is proposed. As a result, the depth information can be recovered from a single image using spectral energy with known internal camera parameters. Unlike previous DFD methods, our method does not model spread functions with Gaussian functions. The direct usage of the spectral energy as the amount of blurriness eliminates the modeling error existent with the Gaussian function-based approaches. The experiments using an uncalibrated commercial digital camera have validated the proposed method and shown a considerably good accuracy in depth recovery.
Subjects
Depth recovery
defocus blur
Depth from defocus
spectral energy
point spread function
line spread function
Type
thesis
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