关键词: 无人机影像, 空间熵, 频谱熵, 拼接质量, 拼接效率

Abstract: Aiming at the problems that the number of image processing has increased sharply and some images have poor quality due to UAVs low flight height, small field of view and small image size, this paper proposes a quick mapping method of UAV images based on dubbed spatial-spectral entropy-based quality algorithm. Firstly, the unmanned aerial vehicle image is sampled and segmented to extract the spatial entropy and spectral entropy information of the local image blocks. Then, SVM and SVR are used for training、prediction and regression to get the final image quality score. Finally, based on the evaluation results, the higher quality image is selected to complete stitching experiment, and the coordinates of the control point are extracted to record the time of the experiment. The experimental results show that the orthophoto generated based on the SSEQ algorithm is close to the accuracy of the orthophoto generated by the original image stitching, and the stitching efficiency is increased by 39.27%. 

Key words: UAV image, spatial entropy, spectral entropy, stitching quality, stitching efficiency