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Published on: June 18, 2021
Spectral matting
Anat Levin1, Alex Rav-Acha, Dani Lischinski
1MIT CSAIL, The State Center 32-D466, Cambridge, MA 02139, USA. alevin@csail.mit.edu
Abstract:
We present spectral matting: a new approach to natural image matting that automatically computes a basis set of fuzzy matting components from the smallest eigenvectors of a suitably defined Laplacian matrix. Thus, our approach extends spectral segmentation techniques, whose goal is to extract hard segments, to the extraction of soft matting components. These components may then be used as building blocks to easily construct semantically meaningful foreground mattes, either in an unsupervised fashion, or based on a small amount of user input.
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