An Improved Edge Detection Algorithm for Noisy Images
Tongping Shen, Fang‐Liang Huang, Jin Li · 2019
On the basis of classical image edge detection algorithm, a new edge detection algorithm is proposed. The number of pulse noise points in detection window of 5 × 5 is counted. For two subzones in each direction of detection window, the mean gray value of non-noise points in every subzone is calculated respectively. Then, the improved Canny algorithm is used to extract the edge features of the target image. Finally, the improved watershed algorithm is used to segment the edge. The experiment results show that directionality of the image edge detected by the new algorithm is well and the edge is fine, and the algorithm can suppress different degree impulse noise and has a certain suppression effect on Gaussian noise and strong adaptability.