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- Title
基于改进PSO-SIFT算法的油田遥感图像匹配.
- Authors
李 宏; 王 鹏; 毕 波; 唐锦萍
- Abstract
.Aiming at the problem that the position scale orientat ion-scale invariant feature transform (PSO-SIFT) algorithm was difficult to find enough correct corresponding relations for oilfield remote sensing images in the case of obvious differences in gray levels, and it took a long time, \Ve proposed an image matching algorithm based on improved PSO-SIFT algorithm. Firstly, \Ve adopted the idea of "backing" character block to construct feature descriptors, which reduced the dimension of the feature descriptors. Secondly, we used a matching strategy that combined the bilateral functions for global motion modeling (BF) algorithm and the fast sample consensus ( FSC ) algorithm to eliminate mismatches from the obtained matching pairs and increase the number of correct matches. Finally, \Ve compared the proposed algorithm \vith four similar algorithms and the original PSO-SIFT algorithm. The experimental results sho\v that the proposed algorithm is more accurate than similar algorithms. Compared with the original algorithm, the proposed <ilgorithm not only gu;1rantees the accuracy of image matching, but also increases the number of correct matching pairs by about three times, and shortens the matching time by about 20 s.
- Subjects
IMAGE registration; REMOTE sensing; ALGORITHMS; INFORMATION processing; PATTERN matching; INFORMATION technology; OPTICAL remote sensing
- Publication
Journal of Jilin University (Science Edition) / Jilin Daxue Xuebao (Lixue Ban), 2021, Vol 59, Issue 2, p342
- ISSN
1671-5489
- Publication type
Article
- DOI
10.13413/j.cnki.jdxblxb.2020128