A New Image Restoration Algorithm Based on Mathematical Morphology and Wavelet Neural Network

摘要：

　　Wavelet neural network (WNN) is introduced into the field of image restoration due to the excellent local feature and adaptive ability.The procedure of restoration can be looked as an approximating procedure from noisy image to original image.The better WNN has approximation performance,the better restoration performance.With the help ofwavelet neural network and mathematical morphology,a new image restoration algorithm is proposed.It can effectively maintain the image edges and details.In order to overcome the shortcomings of the filter with fixed structure,amoeba structure element is presented based on mathematical morphology.Image data is extracted by amoeba structure element,and input into the wavelet neural network.The WWN is trained by BP algorithm in batch mode training,which adjusts the wavelet coefficient and network weights adaptively.The experimental results showed that the approach proposed can preserve fine details and excellent fidelity and is better than general denoising methods.

关键词： Sea clutter Wavelet neural network Amoeba structure element Image restoration

作者: Yan Shen Ming Liu Jinbao Wang Wenlu Zhou

作者单位: College of Science Harbin Engineering University Harbin,150001,China

会议类型: 国际会议

会议名称: 2012 2nd International Conference on Computer Application and System Modeling(2012第二届计算机应用与系统建模国际会议)(ICCASM-2012)

会议地点: 沈阳

会议语种:英文

页码: 1036-1039

在线出版日期: 2012-07-27（万方平台首次上网日期，不代表论文的发表时间）