Image Denoising Based on Hybrid Fourier and Neighborhood Wavelet Coefficients

摘要：

　　Image denoising is a classical topic and a difficult problem in the field of image processing.Fourier transform can effectively sparsely represent the smoothing texture part of the image,but cant effectively represent mutations in the image.The wavelet transform can sparsely represent sharply changing parts in the image,but cant effectively represent the texture and the slowly changing parts of the image.A new method based on hybrid Fourier and neighborhood wavelet coefficient is presented,and experiments show that the method is valid and can improve the visual effect,and that the objective indicator PSNR is better than NeightShrink method.

关键词： image denoising Fourier transform neighboring wavelet coefficients PSNR

作者: Jun Cheng Songli Lei

作者单位: College of Physical and Information Science,Hunan Normal University,Changsha,China Hunan Art Professional College,Changsha,China

会议类型: 国际会议

会议名称: the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT-2012)(2012年电机工程与信息技术国际会议)

会议地点: 沈阳

会议语种:英文

页码: 2258-2262

在线出版日期: 2012-09-26（万方平台首次上网日期，不代表论文的发表时间）