【摘要】 图像的边缘检测是图像处理领域的基本问题。针对小波变换模极大值法检出边缘不连续的问题，引入形态学的处理方式，增强边缘连续性。针对传统Sobel算法检测精度低且采用固定阈值的问题，提出一种结合自适应阈值和增加检测梯度的改进方法。结合形态学小波变换和改进的Sobel算法的优点，通过算法融合的方式，提出了一种将两者融合的图像边缘检测方法。仿真结果表明，该方法提高了边缘检测的精度和连续性，更好地满足了图像边缘定位稳定可靠的要求。更多还原

【Abstract】 Image edge detection is a fundamental problem in the field of image processing. Aiming at the problem of edge discontinuity detected by wavelet transform modulus maximum method, morphological processing method is introduced to enhance the edge continuity. For the problem of low detection accuracy and the use of fixed threshold of traditional Sobel algorithm, an improved method combining adaptive threshold and increasing detection gradient is proposed. Combining the advantages of morphological wavelet transform and improved Sobel algorithm, an image edge detection algorithm that combines the two is proposed by means of algorithm fusion. Simulation results show that the proposed method improves the accuracy and continuity of edge detection, better meeting the needs of stable and reliable image edge positioning.更多还原