Image Denoising based on Wavelet Support Vector Machine

摘要：

In this paper,a new image denoising method based on wavelet analysis and support vector machine regression (SVR) is presented.The feasibility of image denoising via support vector regression is discussed and an illustrative example is given.The wavelet kernel is proposed to construct wavelet support vector machine (WSVM) that could approximate arbitrary function accurately.With the WSVM the noise for image is removed via approximate the image as a 2 dimensional continuous function.The result of experiment shows that the method proposed in this paper based on WSVM can reduce noise better than Gaussian KBF SVM and other traditional methods.

关键词： Image denoising Support vector machine Wavelet analysis Function approximation

作者: Gengqiang Shi

作者单位: College of Medical Instrument and food engineering,University of Shanghai for Science and Technology,Shanghai 20093,China

会议类型: 国际会议

会议名称: 2011 3rd International Conference on Computer and Network Technology(ICCNT 2011)(2011第三届IEEE计算机与网络技术国际会议)

会议地点: 太原

会议语种:英文

页码: 169-172

在线出版日期: 2011-02-26（万方平台首次上网日期，不代表论文的发表时间）