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Content Provider | IEEE Xplore Digital Library |
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Author | Joshi, N. Szeliski, R. Kriegman, D.J. |
Copyright Year | 2008 |
Description | Author affiliation: Univ. of California, San Diego, La Jolla, CA (Joshi, N.) |
Abstract | Image blur is caused by a number of factors such as motion, defocus, capturing light over the non-zero area of the aperture and pixel, the presence of anti-aliasing filters on a camera sensor, and limited sensor resolution. We present an algorithm that estimates non-parametric, spatially-varying blur functions (i.e., point-spread functions or PSFs) at subpixel resolution from a single image. Our method handles blur due to defocus, slight camera motion, and inherent aspects of the imaging system. Our algorithm can be used to measure blur due to limited sensor resolution by estimating a sub-pixel, super-resolved PSF even for in-focus images. It operates by predicting a ldquosharprdquo version of a blurry input image and uses the two images to solve for a PSF. We handle the cases where the scene content is unknown and also where a known printed calibration target is placed in the scene. Our method is completely automatic, fast, and produces accurate results. |
Starting Page | 1 |
Ending Page | 8 |
File Size | 7631069 |
Page Count | 8 |
File Format | |
ISBN | 9781424422425 |
ISSN | 10636919 |
DOI | 10.1109/CVPR.2008.4587834 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2008-06-23 |
Publisher Place | USA |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Image edge detection Image resolution Kernel Image sensors Spatial resolution Layout Cameras Calibration Pixel Filters |
Content Type | Text |
Resource Type | Article |
Subject | Computer Vision and Pattern Recognition Software |
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