中文摘要：

为了使图像边缘检测算法的抗噪声能力更强，能检测到更加丰富的边缘信息，在多尺度形态学边缘检测算法的基础上，提出一种抗噪的多尺度形态学边缘检测算法。一方面，用小波变换法替代常用的加权平均法来融合各尺度下获取的边缘图像，对小波分解后得到的低频系数和高频系数分别采取不同的融合策略，从而有效地保留边缘的细节信息，使得融合后获得的图像清晰且细节丰富。另一方面，在用不同尺度的结构元素检测图像边缘时都采用抗噪的检测算法，因此，该算法具有较强的抗噪声能力。仿真结果表明，该算法既能有效地降低噪声对检测结果的影响，又能获得较理想的边缘图像。

英文摘要：

To reinforce the noise resistance capability of image edge detection algorithm better and refine edge information detection, a multi-scale morphology algorithm for image edge detection with noise re- sistance is proposed. Moreover, wavelet transform method is utilized to replace the commonly used weighted mean method and the edge images are obtained by each scale fused. The low frequency and high frequency coefficients of the wavelet decomposition are adopted respectively by different fusion strategies. Thus the edge details are effectively preserved. The fused image is clear and has rich details. Anti-noise detection algorithm is used to detect the edge of image using different scales of structuring elements. Hence, the algorithm becomes robust to the noise. The simulation result shows that the proposed algo- rithm can effectively reduce the influence of noise on detection results obtaining the ideal edge image.