Journal
IEEE GEOSCIENCE AND REMOTE SENSING LETTERS
Volume 13, Issue 8, Pages 1079-1083Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/LGRS.2016.2565706
Keywords
Airport detection; Fisher vector (FV); line segment detector (LSD); remote sensing images (RSIs); scale-invariant feature transform (SIFT) features; support vector machines (SVMs)
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In this letter, a two-stage method for airport detection on remote sensing images is proposed. In the first stage, a new algorithm composed of several line-based processing steps is used for extraction of candidate airport regions. In the second stage, the scale-invariant feature transformation and Fisher vector coding are used for efficient representation of the airport and nonairport regions and support vector machines employed for classification. In order to evaluate the performance of the proposed method, extensive experiments are conducted on airports around the world with different layouts. The measures used in the evaluation are accuracy, sensitivity, and specificity. The proposed method achieved an accuracy of 94.6%, which was benchmarked with two previous methods to prove its superiority.
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