In the actual processing of veterinary B-ultrasound image enhancement, since the information to be expressed by veterinary B-ultrasound images is different and the enhancement targets are different, the selection of threshold is particularly important for the grayscale-based fuzzy enhancement method. The most appropriate threshold is not fixed for different images. This requires the selection of the best threshold to be determined on the basis of this theory.

There are many methods for automatic threshold selection of veterinary B-ultrasound systems. For example, the image binarization method that can better retain the edge of veterinary B-ultrasound images, the histogram frequency value method suitable for image histograms with obvious peaks and valleys, and the iterative method for selecting thresholds suitable for medical cell images. According to the characteristics of veterinary B-ultrasound images, an automatic threshold selection method suitable for veterinary B-ultrasound image processing-the maximum entropy method was selected. It is also confirmed that adding this automatic threshold selection method to the grayscale-based fuzzy enhancement method can more conveniently and quickly achieve the selection of the best threshold. Therefore, this enhancement method can be used to process veterinary B-ultrasound images faster and better.

The original unprocessed veterinary B-ultrasound images have average clarity, and the overall color and brightness are not very good, a bit dark, especially the extraction effect of the nodule center and edge parts that we need to highlight is not very good.

Some people have found that these six enhancement methods can enhance the image quality to a certain extent, among which the grayscale fuzzy enhancement method is particularly effective in controlling the overall brightness of the image, making the veterinary B-ultrasound images look brighter but not distorted, and the nodule center and edge parts that need to be highlighted are significantly enhanced, and look clearer than the original veterinary B-ultrasound images.

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