To solve the problems of the inability of LCM in detecting damaged targets in local bright areas and its low separation efficiency, a damage detection method based on local contrast image enhancement of a neighborhood vector local dot was proposed in this study. First, a nine-dimensional neighborhood vector was generated from the 3×3 neighborhood of each point in the image, and the maximum value in the neighborhood was extended to the nine-dimensional extreme vector in calculating the dots of the neighborhood vector and extreme vector. Second, the Neighborhood Vector Dot Contrast (NVDC) of each pixel was calculated. Third, the NVDC of the image patch of each pixel was calculated,i.e., the maximum NVDC value of each pixel in a relatively large area(5×5) was taken as the final Neighborhood Vector Dot Local Contrast (NVDLC) of the corresponding pixel. Fourth, the NVDLC image was binarized, and the targets were separated from the background. The experimental results demonstrate that the LSNR of the damaged image is improved from 3.775 to 12.445, and the signal of the damage target is significantly enhanced using the image enhancement method proposed in this study. After the maximum contrast image of NVDLC is enhanced, the damage targets with size of less than 2 pixels can be directly separated from the background using the adaptive threshold formula, which meets the accuracy and efficiency requirements of the weak contrast damage target detection.