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Matching improvement of satellite images using geometric relationships
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Ali Jafari *   , Elham Pour Yaghoubi |
| Maleke-Ashtar University |
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Abstract: (1576 Views) |
Matching remote sensing images is a challenging issue in computer vision applications. Due to the very large dimensions, local destructions, radiometric distortions, and geometric changes in the input images, the existing matching algorithms such as Scale Invariant Feature Transform (SIFT) produce a large number of false matches. Moreover, due to the high dimensional images a big number of keypoints are extracted in large-scale satellite images. A very large number of keypoints increases the computational, memory and time complexity in the stages of feature description and matching the keypoints. In this paper, the geometric relationships between the key points extracted from the input images, are used to improve the detection process of false corresponding points and also to increase the speed of the SIFT algorithm. The proposed false correspondence removal algorithm uses the histogram of the scale difference values and the two image rotation angle. In the following, two new algorithms which are based on the hierarchical strategy are proposed to increase the speed of the SIFT algorithm. The first proposed algorithm is based on finding the optimal octaves in the scale space of the SIFT algorithm and selecting their compared keypoints. In the second method, the parameters of the affine transformation which are between the two images are calculated by performing an initial matching, and then this transformation is used to reduce the search space in the final matching stage of the keypoints. Finally, to check the performance and accuracy of each of the proposed methods, a variety of simulated and real images have been used. Moreover, for the final evaluation of the proposed algorithms, the obtained results are compared with SIFT, SR-SIFT and SIFT-GSI methods. The experimental results confirm the accuracy, stability and high speed of the proposed methods in matching satellite images.
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| Keywords: Image Matching, Affine Transformation, Reduce Search Space, SIFT Algorithm |
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Full-Text [PDF 815 kb]
(487 Downloads)
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Type of Study: Research |
Subject:
Aerial Photogrammetry
Received: 2022/12/11 | Accepted: 2024/01/3 | ePublished ahead of print: 2024/02/18 | Published: 2024/03/4
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