Blind Separation for Blurred Images Based on the Adaptive Nonholonomic Natural Gradient Algorithm

摘要：

A blind separation algorithm for restoring the original images from the blurred grayscale images is proposed, which utilizes the constrain ability of the nonholonomic natural gradient (NNG) in the independent component analysis(ICA) methods. However, the nonlinear activation function of this algorithm relates to the unavailable probability distribution of the sources closely, though it is robust to nonstationary and strongly undulate sources. To this problem, our method adaptively select the nonlinear function by use of the kurtosis of the output signals, and propose an adaptive NNG (ANNG) blind separation algorithm of blurred image based on ICA, and research the effect of the different mixture matrices to the performance of this algorithm. The simulations show the validity of the proposed method. Compared with the nonholo nomic natural gradient algorithm and the classical FastICA algorithm, the performance index of this paper algorithm is also better.

作者: Y. L. Niu J. C. Ma Y. Wang

作者单位: School of Marine,Northwestern Polytechnical University,Xian 710072,China School of Electronic & Information Northwestern Polytechnical University,Xian 710072,China

会议类型: 国际会议

会议名称: The 2nd International Symposium on Systems and Control in Aeronautics and Astronautics(第二届航空航天系统与控制国际会议 ISSCAA 2008)

会议地点: 深圳

会议语种:英文

页码: 173-176

在线出版日期: 2008-12-10（万方平台首次上网日期，不代表论文的发表时间）