The changes in lighting conditions in images can have an impact on edge detection. In cases of uneven or strong lighting changes, edge detection becomes more difficult. In order to achieve effective edge detection of optical images, a fuzzy mathematics based adaptive edge detection method for optical images is proposed. Using a compensation function to compensate for the illumination of optical images, enhancing their brightness, and then linearly adjusting and converting the brightness ratio of the images. By using homomorphic filtering methods to adjust the illumination and reflection components of optical images, the clarity of optical images can be improved. Combining wavelet transform method and adaptive dual threshold method to extract edge points from optical images, the fuzzy C-means method in fuzzy mathematics is used to cluster the extracted optical image edge points, obtain optical image edges, and achieve adaptive detection of optical image edges. The experimental results show that the DBI index of the proposed method is 0.21, the CHI index is 0.97, and the highest F-Measure value is 0.98, indicating good image processing performance and high edge detection accuracy, making it suitable for adaptive edge detection of optical images.