Abstract: Recently, researches on the agricultural image processing of fruit, plant and insect were conducted mostly using the traditional methods. These methods cannot be used to analyze the image in the time and frequency domain simultaneously, and do not have the multiresolution characteristics. Therefore, a new theory and method—wavelet transform was used to conduct the research on agricultural image enhancement. In the paper, wavelet transform was applied to low contrast image enhancement of Xiankelai flower and sectional view of orange, and an algorithm that enhances low frequency and eliminates high frequency and another algorithm that enhances low frequency and combines original image were designed to solve some problems failing to enhance the image very well using traditional histogram equalization, log transform and LoG Filter methods. And wavelet transform was applied to image enhancement of Chinese date that has gauffers and cracks, which makes the Chinese date gauffers and cracks well-defined to facilitate classification and detection. These results prove that agricultural image enhancement algorithm based on wavelet transform is satisfying.