DocumentCode :
1362533
Title :
Removal of Partial Occlusion from Single Images
Author :
McCloskey, Scott ; Langer, Michael ; Siddiqi, Kaleem
Author_Institution :
Sch. of Comput. Sci., McGill Univ., Montreal, QC, Canada
Volume :
33
Issue :
3
fYear :
2011
fDate :
3/1/2011 12:00:00 AM
Firstpage :
647
Lastpage :
654
Abstract :
This paper examines large partial occlusions in an image which occur near depth discontinuities when the foreground object is severely out of focus. We model these partial occlusions using matting, with the alpha value determined by the convolution of the blur kernel with a pinhole projection of the occluder. The main contribution is a method for removing the image contribution of the foreground occluder in regions of partial occlusion, which improves the visibility of the background scene. The method consists of three steps. First, the region of complete occlusion is estimated using a curve evolution method. Second, the alpha value at each pixel in the partly occluded region is estimated. Third, the intensity contribution of the foreground occluder is removed in regions of partial occlusion. Experiments demonstrate the method´s ability to remove the effects of partial occlusion in single images with minimal user input.
Keywords :
curve fitting; hidden feature removal; image restoration; alpha value; blur kernel convolution; curve evolution method; partial occlusion; photographic images; pinhole projection; Apertures; Cameras; Convolution; Lenses; Mathematical model; Noise; Pixel; Focus; curve evolution.; matting; partial occlusion; Algorithms; Artificial Intelligence; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Pattern Recognition, Automated; Sensitivity and Specificity; Subtraction Technique;
fLanguage :
English
Journal_Title :
Pattern Analysis and Machine Intelligence, IEEE Transactions on
Publisher :
ieee
ISSN :
0162-8828
Type :
jour
DOI :
10.1109/TPAMI.2010.187
Filename :
5611540
Link To Document :
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