@conference {33211,
	title = {Graph-Based regularization for color image demosaicking},
	booktitle = {Proc.. IEEE International Conference on Image Processing},
	year = {2012},
	month = {Sep.},
	address = {Orlando, FL},
	abstract = {We present a novel regularization framework for demosaicking by viewing images as smooth signals defined on weighted graphs. The restoration problem is formulated as a minimization of variation of these graph-domain signals. As an initial step, we build a weight matrix which measures the similarity between every pair of pixels, from an estimate of the full color image. Subsequently, a two-stage optimization is carried out: first, we assume that the graph Laplacian is signal dependent and solve a non-quadratic problem by gradient descent; then, we pose a variational problem on graphs with a fixed Laplacian, subject to the constraint of consistency given by available samples in each color channel. Performance evaluation shows that our approach can improve existing demosaicking methods both quantitively and visually, by reducing color artifacts.},
	author = {Chenhui Hu and Lin Cheng and Yue M. Lu}
}
