Gradient Color Tensor based Approach for Spectral Matting
Adam Ghorbel, Marwen Nouri, Emmanuel Marilly · 2013
Image matting aims to extract foreground objects from a given image in a fuzzy mode. One of the major state-of-the-art methods in this field is spectral matting. It automatically computes fuzzy matting components by using the smallest eigenvectors of a defined Laplacian matrix that is generated from affinities computation between adjacent pixels in an image. Results obtained by such approach are coarsely related to the ability of defining an affinity matrix that it should be able to well separate between different pixels’ clusters. To accomplish better matting and get better results, we propose a new spectral matting approach. We use a color tensor gradient of color images in order to enhance the affinity computation