Introduction - If you have any usage issues, please Google them yourself
Any picture would be affected by all kinds of noise during the course of acquisition and transition which would lead to the degradation of a picture. The image and the character of a picture indistinct which is an disadvantage for image analysis. The way for lower down the noise to improve the quality of the picture calls the smoothing of image or denoising . It can be accomplished in spatial domain and frequency domain. A more common formula of templates used in image smooth denoising is developed from Gauss function in order to offer more templates to be chosen when denoising images with random noise. For each image with different levels of noise, only one template corresponding to the level of this image noise is optimal when denoising this image. The methods of smoothing processing are given in this paper .And the showing results are presented and they validate the above formula and conclusions.