Abstract:

Objective: In order to solve the problems of frequent occurrence of slow matching speed, high error matching rate and poor matching quality when processing aerial photographic images in forests of UAV in low altitude by directly using photogrammetric software, the article started from the aerial photographic image features in forests in low altitude to explore an image matching strategy suitable for UAV's aerial photographic images in forests. Method: The homography restraints among image pairs were built with the aid of UAV's POS data based on the related principles of photogrammetry and computer vision. This is a partition matching strategy of which several corresponding subareas are divided according to certain location distribution rules and each sub area is regarded as an independent image to be processed during the feature extraction and matching processes. Meanwhile the GIS space analysis algorithm was introduced into the feature matching processes to explore the characterization and evaluation of location distribution quality of feature points. Result: Under the software programming environments of the same work station Python 3.7 and OpenCV 3.4.2.16, the contrast experiment was implemented by using the six kinds of characteristic operators of ORB, FAST, SURF, SIFT, KAZE and AKAZE, with collaboration of the partition matching strategy and the sampling matching strategy under the common classification to the aerial photographic images of broad-leaved forest and coniferous forest with the same parameters set. The results showed that the average matching speed of the six kinds of operators in collaboration with partition matching strategy was increased by 11.53%, the average matching rate was increased by 0.83%, and the average location distribution quality was improved by 2.46%. Conclusion: The low altitude UAV's forest images presented different features from the common mapping aerial photographic images, where the matching methods of the common mapping images couldn't be used discriminately. The partition matching strategy of the original resolution rate images used by this article narrowed matching scope and increased matching speed while keeping the image details; meanwhile this strategy improved the location distribution quality of the feature points and lowered the error matching rate by using the homography restraints built with UAV's POS data. The effectiveness and flexibility of this strategy was verified by collaborating with the experiments of the six kinds of characteristic operators and the irrelevant independence from the characteristic operators. The optimal effect result collaborating with the strategy by AKAZE operator was obtained, which could provide references for the related studies of the aerial photographic image processing in forests.

Key words: UAV, forest image, feature matching, matching strategy