DocumentCode :
3489941
Title :
Self-Similarity Inpainting
Author :
Ardis, Paul A. ; Brown, Christopher M.
Author_Institution :
Comput. Sci. Dept., Univ. of Rochester, Rochester, NY, USA
fYear :
2009
fDate :
7-10 Nov. 2009
Firstpage :
2789
Lastpage :
2792
Abstract :
We present a novel means of texture inpainting, dubbed self-similarity inpainting, that uses the self-similarity descriptor to implicitly encode complex structures through a summary of local neighborhood comparisons. Pixel patches are selected from a codebook based on descriptor distance in their original locale and after the proposed insertion. We suggest an efficient means of parallelizing this approach across an arbitrarily large number of processors, as well as describing improvements over existing techniques and extensions that shift the tradeoff between inpainting quality and algorithmic efficiency for object or artifact removal. Results are shown for a number of synthetic and captured digital images, including effects upon human foveal attention.
Keywords :
image coding; image motion analysis; image restoration; image sampling; image texture; artifact removal; codebook; descriptor distance; image restoration; image sampling; local neighborhood comparisons; object removal; pixel patch; self-similarity descriptor; self-similarity inpainting; texture inpainting; Computational efficiency; Computer science; Degradation; Digital images; Humans; Image restoration; Image sampling; Image segmentation; Pixel; image restoration; image sampling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2009 16th IEEE International Conference on
Conference_Location :
Cairo
ISSN :
1522-4880
Print_ISBN :
978-1-4244-5653-6
Electronic_ISBN :
1522-4880
Type :
conf
DOI :
10.1109/ICIP.2009.5414184
Filename :
5414184
Link To Document :
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