图像的边缘检测在实际生活中广泛应用, 但其检测结果仍存在细节丢失问题。为此提出一种新的图像边缘检测算法。首先, 采用二维二进制小波变换, 对图像进行预处理；然后, 结合一种新的自适应双阈值算法, 检测出图像的边缘点；最后, 采用改进的数学形态学梯度检测算法, 对图像的边缘信息进行进一步检测。通过仿真实验得出, 新算法能够检测到更丰富的图像边缘信息, 使图像的边缘提取更清晰、细腻；与单一形态学算法相比, 新算法使图像的均方误差值大幅度降低、峰值信噪比提高了2.3 dB。

Image edge detection has been widely used in practical applications, but the details of images are lost in the detection result. To solve the problem, a new image edge detection algorithm was proposed. Firstly, the two-dimensional binary wavelet transform was used to pre-process the image. Then, the edge points of the image were detected by using a new adaptive dual-threshold algorithm. Finally, an improved mathematical morphological gradient detection algorithm was used to further detect the edge information of the image. The simulation results show that: 1) The new algorithm can detect more edge information of the image, and the extracted edge of the image is more clear and delicate;and 2) Compared with single morphological algorithms, this algorithm greatly decreases the mean-square error value of the image and increases the peak signal-to-noise ratio by 2. 3 dB.