DocumentCode :
249309
Title :
Automatic defocus spectral matting
Author :
Hui Zhou ; Ahonen, T.
Author_Institution :
Nokia Res. Center, Nokia USA Inc., Sunnyvale, CA, USA
fYear :
2014
fDate :
27-30 Oct. 2014
Firstpage :
4328
Lastpage :
4332
Abstract :
Alpha matting for single image is an inherently under-constrained problem and thus normally requires user input. In this paper, an automatic, bottom-up matting algorithm using defocus cue is proposed. Different from most defocus matting algorithms, we first extract matting components by applying unsupervised spectral matting algorithm on single image. The defocus cue is then used for classifying matting components to form a complete foreground matte. This approach gives more robust result because focus estimation is used in component level rather than pixel level.
Keywords :
image classification; alpha matting; automatic defocus spectral matting; bottom-up matting algorithm; component level; defocus cue; matting component classification; unsupervised spectral matting algorithm; Algorithm design and analysis; Benchmark testing; Cameras; Cost function; Estimation; Image color analysis; Laplace equations; Defocus; alpha matting; focal stack; matting Laplacian; spectral matting;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2014 IEEE International Conference on
Conference_Location :
Paris
Type :
conf
DOI :
10.1109/ICIP.2014.7025879
Filename :
7025879
Link To Document :
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