基于小波变换的含噪图片的自适应边缘提取

对含有白噪声的图片的边缘提取进行了讨论。利用噪声图像小波系数的统计特征和小波变换的多尺度特性构造收缩因子，通过收缩因子对图片中的噪声和边缘区别对待。而且通过极大似然法估计小波系数概率模型中的三个参数，使算法达到自适应性。利用所讨论的理论对一幅含有噪声的图像进行边缘提取实验，结果令人满意。

Wavelet-Based Self-Adaptive Edge Detection for Noisy Aerial Image

An algorithm used to detect aerial image's edge contaminated by addictive white noise is discussed. Using statistical characteristic of contaminated aerial image's wavelet coefficients and multi resolution decomposition of wavelet transform, shrinkage factors are constructed and used for treating the edge or noise separately. Furthermore, by evaluating three parameters of wavelet coefficients' probability model using maximum likelihood method, self adaptively of the algorithm is achieved. The result of the detecting edge of contaminated aerial image by this method is satisfactory .