Edge detection method for noisy images based on improved Canny operator
An edge detection method was designed explicitly for noisy images utilizing improved Canny operators to tackle the issue of inadequate visual effects in images resulting from low-quality edge detection and failure to accurately extract the real edge in noisy conditions.This study used an improved Retine algorithm to extract enhanced reflection images,which were then denoised and smoothed using an anisotropic diffusion filtering technique.Edge detection was carried out on the smoothed images based on gradient amplitude dual threshold from the optimized Canny operators,significantly improving edge detection performance.Experimental results demonstrated that after applying this denoising method,the images achieved a signal-to-noise ratio of 57.96,a root mean square error of 3.12e-04,and a reduction in the noise index from approximately 1 to around 0.13.The enhanced images displayed no halo effects but improved clarity in darker regions,with no interruptions in edge detection or false edges.These findings suggested that this approach effectively achieves good image denoising while maintaining sharpness in edges,thereby enhancing the overall visual quality of the images.
万方数据
维普
