Abstract: Aiming at the shortcomings of traditional Canny operator in filtering, which can blur the edge and need to set high and low thresholds manually, an improved adaptive threshold Canny edge detection algorithm based on 3D block matching is proposed for terahertz 3D tomography. On one hand, the algorithm improves the filtering method by replacing the Gaussian filtering algorithm with the 3D block matching (BM3D) filtering algorithm and the guided filtering algorithm to reduce the loss of image edge information. On the other hand, in view of the uncertainty of the traditional manual threshold, the maximum inter-class variance method (OTSU) is used to adaptively determine the high and low thresholds of 3D image blocks after block matching of gradient images. Finally, the edge detection of images containing noise is carried out using the algorithm. It is found that when the Gaussian noise variance is 20, the filtered peak signal-to-signal ratio (PSNR) increases from 22.202 to 27.151, which verifies the effectiveness of the algorithm in removing noise. By using BM-OTSU-Canny algorithm, the number of false edges is reduced, and at the same time, the edge points with better connectivity can be retained, and the extraction effect of edge details is improved.

Key words: image processing, terahertz imaging, 3D block matching, Canny algorithm, edge detection