Blind Image Extraction by Using Local Smooth Information
Mao Ye, Yongguo Liu, Ming Liu, Fan Li, Qihe Liu · 2009
This paper proposes a new approach to blind image extraction. By using the property that most of near pixels are smooth, blind image extraction is formulated to a generalized eigen-decomposition problem. The key point of our method is the formulation of matrix pencil. Since the image is two dimensional, the values of a small patch are smooth. Based on this observation, two mixed signals are formulated in columnwise order or in rowwise order respectively. The matrix pencil is constructed by using these two mixed signals. The separation weight vector can be obtained by generalized eigen-decomposition. Compared with the 'Non-Negative ICA' algorithm, the original signals in our algorithm are not required to be well-grounded, which means that they have a non-zero pdf in the region of zeros. In contrast to many second order methods in recent literatures, the two dimensional signals are used. Simulation results on mixed images are employed to further illustrate the advantages of our approach.