There are often significant intensity variations between multispectral images, making automatic registration tasks difficult. Traditional feature matching methods, such as the scale-invariant feature transform (SIFT), are often sensitive to nonlinear variations of intensity between multispectral images. To solve this problem, an improved SIFT algorithm is introduced. First, the contrast limited adaptive histogram equalization algorithm is introduced in the feature extraction stage to improve the feature point extraction results. Then, the Sobel operator is used to enhance the main direction consistency between homologous feature point pairs. The experimental results suggest that the method can obtain reliable registration results on unmanned aerial vehicle multispectral images.