Image De-Noising Based On Improved Data-Adaptive Kernel Regression Method

摘要：

　　This paper proposes a novel method for image de-noising,the algorithm is improved the data-adaptive kernel regression method.The process of each pixel is:first determine whether the pixel is on boundary,for the pixels on the edge to establish the kernel which shape is adaptive with the boundary,and then use iterative process for de-noising.For non-boundary pixels,use the data-adaptive iterative kemel regression method.Experiments have shown promising results in image de-noising; the algorithm is able to filter out the high-frequency noise of image while it retains the details of the image characteristics.

关键词： kernel regression de-noising data-adaptive edge adaptive

作者: Zhenping Qiang Xu Chen Hong Lin Tonglin Zhao

作者单位: Department of Computer and Information Science, Southwest Forestry University, Kunming, China

会议类型: 国际会议

会议名称: 2012 2nd international Conference on Materials Science and Information Technology(2012第二届材料科学与信息技术国际会议)(MSIT2012)

会议地点: 西安

会议语种:英文

页码: 1359-1364

在线出版日期: 2012-08-24（万方平台首次上网日期，不代表论文的发表时间）