文件名称:Imattinfrom
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Image matting is the extraction of a foreground object from
an image and determination of the transparency of each pix-
el. Matting is inherently an ill-posed and underconstrained
problem. Therefore, some assumptions need to be made to
solve it. Recent methods that provide a closed-form solution
to this problem are based on the assumption of either local
smoothness or the nonlocal principle, but they cannot always
produce satisfactory matting results. In this paper, we pro-
pose a K-nearest neighbors (KNN)-based color line model
that combines and preserves the advantages of both the above
assumptions. The experimental matting results indicate that
they are of comparable or higher quality than those obtained
by the existing methods based on the above two assumptions.
an image and determination of the transparency of each pix-
el. Matting is inherently an ill-posed and underconstrained
problem. Therefore, some assumptions need to be made to
solve it. Recent methods that provide a closed-form solution
to this problem are based on the assumption of either local
smoothness or the nonlocal principle, but they cannot always
produce satisfactory matting results. In this paper, we pro-
pose a K-nearest neighbors (KNN)-based color line model
that combines and preserves the advantages of both the above
assumptions. The experimental matting results indicate that
they are of comparable or higher quality than those obtained
by the existing methods based on the above two assumptions.
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jin2013.pdf
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