Woodland aerial images captured by UAV(unmanned aerial vehicle) possess high resolution, large amount of pictures, plenty of edges. These features increased the error rate of image registration. In this paper, a new image stitching method based on lacunarity in fractal geometry was proposed. Lacunarity can describe the roughness of texture. We calculated lacunarity value from blocks in image and found several candidate blocks, which were used to extracte the feature points instead of the whole image. This method made contributions to reducing matching feature points amount and improving the accuracy when registration. We used global mosaic method instead of traditional method in the step of image transformation to decrease error accumulation spreading caused by transformation matrix multiplication. The experimental results showed that, when dealing with high resolution UAV image shot from different heights, compared with traditional SURF and down-sample stitching method, the proposed method gave a promising and an excellent visual effects result without losing resolution, and the value of RMSE was better.