The quality of UAV image is closely related to light, imaging angle and the feature of the ground object. There are some shortcomings in many images, such as poor visual contrast, large distortion and insufficient resolution, which cause many difficulties in subsequent image matching and orthorectification. To obtain better results in UAV image matching, the authors first calculated the degree of dispersion between gray value of pixel and image gray average to divide the image into different areas according to the discrete gray information of original images. Then, the distance weighted interpolation method was used to calculate the transformation function and enhanced the various regions in different degrees. After that, the histogram of enhanced image was corrected. Finally, the epipolar constraint method was used in the image matching experiment. The results show that, because of the enhanced image gray value gradient difference, there exists some extent of increased matching success rate and uniformity in the woodland area which has smaller gray change, thus favoring the smooth progress of the work of subsequent image processing.
唐敏, 李永树, 李歆, 刘波. 无人机影像局部增强方法及其在影像匹配中的应用[J]. 国土资源遥感, 2013, 25(4): 53-57.
TANG Min, LI Yongshu, LI Xin, LIU Bo. Local enhancement method and its applications to UAV image matching. REMOTE SENSING FOR LAND & RESOURCES, 2013, 25(4): 53-57.
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2013, Vol. 25 
