Median filtering has a certain inhibitory effect on pulse noise and salt and pepper noise in veterinary B-ultrasound systems, but it also filters out some useful information and does not handle the details of veterinary B-ultrasound images very well. Its working steps are as follows: move the template in the image and overlap the center of the template with a certain pixel position in the image; read the grayscale values of each corresponding pixel under the template; arrange these grayscale values in a column from small to large; find the one in the middle of these values; assign this middle value to the pixel at the center of the corresponding template.

Adaptive filtering has a good inhibitory effect on Gaussian noise and salt and pepper noise in veterinary B-ultrasound systems, and better retains the useful information in the image, and its effect is better than median filtering. In veterinary B-ultrasound images, when there are boundaries or other sudden changes in structure, the gray value changes greatly, so its variance is large and the noise variance is small. At the same time, since it is useful information, the signal should be maintained as the main focus. In the area where the gray value is evenly distributed, its variance is mainly determined by the noise, and the noise variance is small, so denoising should be the main focus at this time.

The wavelet denoising method also has a good inhibitory effect on Gaussian noise and salt and pepper noise in the veterinary B-ultrasound system, and because it uses different thresholds for denoising at different scale levels, its effect is better and the veterinary B-ultrasound images are clearer.

In short, by comparing the three methods of denoising veterinary B-ultrasound images, it is concluded that the wavelet denoising method and the adaptive filtering method have good denoising effects, and the wavelet is slightly superior, but the use of wavelet denoising requires the selection of appropriate wavelets and scale levels.