基于第二代小波的增强边缘的图像去噪

传统的一些去噪技术往往是以牺牲图像的边缘和细节为代价的。为了去掉图像的噪声,同时又能够很好地保留图像的边缘和纹理细节,在介绍第二代小波变换的原理的基础上,提出使用边缘检测的方法检测出图像的边缘和纹理细节,将它和该图像进行融合,用第二代小波对含噪图像进行分解,对图像高频进行自适应去噪。由于图像在去噪前融合了边缘信息,因此边缘和细节部分得到了增强。仿真结果表明：该去噪方法优于传统小波阈值去噪方法。

Image Denoising Using Enhanced Edge Information Method Based on Second Generation Wavelet

The traditional denosing methods are often applied at the cost of sacrificing the edge and texture detail of the images.In order to denose and retain the edge and textile detail of the image,this paper proposes a method of enhanced edge information based on the principle of second generation wavelet.First,use the edge detection method to detect the edge and texture detail of the image.Second,fuse the image and its edge and texture detail in order to enhance the parts of edge and texture detail.And then,decompose the fused image by second generation wavelet.Last,make the adaptive threshold denoising for the high frequency of the fused image.The simulation shows that the edge and texture detail of fused image has been enhanced.Comparing to the traditional wavelet threshold denosing method,the method proposed in this paper is much better in improving the visual effects and signal-to-noise.