小波变换在医学图像边缘提取中的应用

边缘是图像的重要特征。医学图像往往较模糊．其边缘特征难以用传统方法检测。小波变换具有良好的局部化特性、多分辨特性．及检测信号局部突变的能力。对图像进行二维小波变换，其梯度模值反映了图像的边缘。介绍一种基于小波变换的图像边缘提取方法。实验证明．与传统边缘检测方法相比，该方法去噪效果好，能提取图像中较弱的边缘，且能使边缘细化。这些特点使得他特别适合于医学图像边缘的提取。

Application of Wavelet Transform in Edges Detection of Medical Image

The most important characteristic of image is edges.Medical image is usually fuzzy, and its edges are difficult to detect by traditional methods. Wavelet transform has good localization feature and multiresolution analysis, and capacity of detecting local signal mutation. When image is transformed by 2dimension wavelet, the abstract value of gradation gives information of the image edge. This paper presents a method of detecting image edges based on wavelet transform. Test shows that the method can detect weak edges from noised image, thin the edges as well. These merits are especially fit for edges detection of medical image.