Abstract
ABSTRACTThe multi-frame images taken by the unmanned aerial vehicle (UAV) in the complex flight environment will be easily affected by the jitter, noise and exposure, which result in the decline of detection rate of the interested regional target. Considering this problem, a super-resolution reconstruction algorithm for aerial multi-frame images of UAV is proposed by using multi-scale non-local dictionary training method based on compressive sensing. Experimental results prove the validity and accuracy of the proposed algorithm.
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