摘要
阐述了一种利用平稳小波变换(SWT)从SAR图像中提取海岸线的方法。该方法首先利用基于局部统计特性的自适应滤波算法对SAR图像进行滤波,然后利用SWT对SAR图像进行分析处理,计算SWT系数的小波梯度信息,通过模极大值搜索检测边缘点,最后利用阈值化和形态学方法对局部极大值图像进行细化处理。实验结果证明,这种方法是对于SAR图像海岸线提取是有效的。
In this paper,a sea boundary extraction method based on stationary wavelet transform in SAR sea images is presented.This method is to reduce Speckle noise by local statistical adaptive denoising firstly,and then Stationary Wavelet Transform（SWT） is applied to process SAR images and its coefficients are used to calculate and generate the Wavelet Gradient Information（WGI）.The sea boundary is obtained by searching the module maximum according to WGI.The morphological thinning algorithm and threshold technique are also used for edge refinement to suppress the other oceanic features such as the isolate Speckle noise.The result of the experiment shows that this method is efficient for sea boundary extraction in SAR satellite images.
出处
《电脑开发与应用》
2010年第5期30-32,共3页
Computer Development & Applications
关键词
平稳小波变换
海岸线提取
小波梯度信息
模极大值
stationary wavelet transform
sea boundary extraction
wavelet gradient information
module maximum
