用于侧扫声纳图像边缘检测的改进Canny算子

摘要： 针对侧扫声纳图像斑点噪声强的特点，提出一种改进的Canny算子进行边缘检测. 根据斑点噪声的乘性模型和瑞利分布特性，在非下采样Contourlet变换域进行局部自适应降斑. 该方法在有效抑制斑点噪声的同时可较好地保护边缘，避免了Canny算子造成的边缘模糊. 计算降斑后图像的梯度值分布，对梯度幅值进行非极大值抑制得到极大值点. 将梯度模的极大值点分成强边缘点、弱边缘点与非边缘点3 类，基于类间方差最大自适应确定区分3 类的双阈值，经双阈值处理与弱边缘连接得到边缘图. 对模拟声纳图像和实际声纳图像的边缘检测结果表明，较之Canny算子和小波模极大等边缘检测方法，该方法具有边缘检测完整、定位准确、伪边缘点较少等优点.

Edge Detection for Side-Scan Sonar Images Based on Improved Canny Operator

To deal with strong speckle noise of side-scan sonar images,an edge detection method based on improved Canny operator is proposed.According to a multiplicative model and the Rayleigh distribution of speckle noise,sonar image de-speckling is performed locally and adaptively in the contourlet transform domain without sub-sampling.This effectively suppresses speckles and better protects edges without blurring due to Gaussian smoothing.Gradients of the de-speckled sonar image are computed.The maximal magnitudes...