Authors:
Yuichi Takeda
1
;
Shinsaku Hiura
2
and
Kosuke Sato
1
Affiliations:
1
Osaka University, Japan
;
2
Hiroshima City University, Japan
Keyword(s):
Computational Photography, Coded Aperture, Stereo Depth Estimation, Deblur, Depth of Field, Refocusing.
Related
Ontology
Subjects/Areas/Topics:
Computer Vision, Visualization and Computer Graphics
;
Image Enhancement and Restoration
;
Image Formation and Preprocessing
;
Image Formation, Acquisition Devices and Sensors
;
Motion, Tracking and Stereo Vision
;
Stereo Vision and Structure from Motion
Abstract:
Image acquisition techniques using coded apertures have been intensively investigated to improve the performance of image deblurring and depth estimation. Generally, estimation of the scene depth is a key issue in the recovery of optical blur because the size of the blur kernel varies according to the depth. However, since it is hard to estimate the depth of a scene with a single image, most successful methods use several images with different optical parameters captured by a specially developed camera with expensive internal optics. On the other hand, a stereo camera configuration is widely used to obtain the depth map of a scene. Therefore, in this paper, we propose a method for deblurring and depth estimation using a stereo camera with coded apertures. Our system configuration offers several advantages. First, coded apertures make not only deconvolution but also stereo matching very robust, because the loss of high spatial frequency domain information in the blurred image is well
suppressed. Second, the size of the blur kernel is linear with the disparity of the stereo images, making calibration of the system very easy. The proof of this linearity is given in this paper together with several experimental results showing the advantages of our method.
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