Image Denoising English Literature and TranslationNew Method for Image Denoising while Keeping Edge InformationEdge information is the most important high- frequency information of an image so we shou

f an image that people pay most attention to is its edges. Therefore, preserving edge information while denoising is crucial for maintaining the quality of the image.

Our proposed method first detects the edges of the image using a suitable algorithm, such as Canny edge detection or Sobel edge detection. Then, the image is divided into two parts: the edge part and the smooth part. The threshold for denoising is set higher for the smooth part, as it contains less important information and can tolerate more denoising. On the other hand, the threshold for denoising is set lower for the edge part, as it contains more important information and needs to be preserved as much as possible.

Experimental results show that our method outperforms traditional wavelet threshold denoising methods in both preserving edge information and improving signal-to-noise ratio. The denoised images retain more details and have sharper edges, making them more visually appealing. Moreover, our method is easy to implement and can be applied to various types of images.

In conclusion, our proposed image denoising method based on edge detection is a promising approach for preserving edge information while removing noise from images. Further research can be done to optimize the algorithm and explore its potential applications in various fields