Title :
Graph-based regularization for color image demosaicking
Author :
Chenhui Hu ; Lin Cheng ; Lu, Yue M.
fDate :
Sept. 30 2012-Oct. 3 2012
Abstract :
We present a novel regularization framework for demosaicking by viewing image as smooth signal on a weighted graph. The restoration problem is formed as a minimization of variation of the signal on graph. 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. After that, a two-stage optimization is carried out: first, we assume that graph Laplacian is signal dependent and solve a non-quadratic problem by gradient descent; then, we pose a variational problem on graph with a static Laplacian, under the constraint of consistency with the available samples in each color component. Performance evaluation shows that our approach can improve the previous demosaicking methods both quantitively and visually, by alleviating the artifical effect. Moreover, the mapping from image to signal on graph provides a general method for image processing.
Keywords :
Laplace transforms; gradient methods; graph theory; image colour analysis; image restoration; image segmentation; matrix algebra; minimisation; smoothing methods; variational techniques; color component; color image demosaicking; gradient descent method; graph Laplacian; graph-based regularization; image processing; image restoration problem; minimization; nonquadratic problem; optimization; signal smoothing; similarity measure; static Laplacian; variational problem; weight matrix; weighted graph; Abstracts; Color; Graphics; Demosaicking; Laplacian; regularization method; weighted graph;
Conference_Titel :
Image Processing (ICIP), 2012 19th IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
978-1-4673-2534-9
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2012.6467473