Robust multi-view UAV SAR image registration based on selective correlation of log gradient descriptor Article Swipe
Xin Xiong
,
Guowang Jin
,
Qing Xu
,
Xiangyun Liu
,
Quanjie Shi
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.jag.2024.103678
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.jag.2024.103678
Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) image characteristics, such as large geometric distortions, striped inhomogeneous radiation, severe speckle noise and ultra-high resolution, pose significant challenges to multi-view UAV SAR image registration. To address these issues, we propose a robust multi-view UAV SAR image registration algorithm based on the selective correlation of the log gradient descriptor. First, slant range UAV SAR images are geocoded using a publicly available digital elevation model to attenuate the topographic distortions. Second, we follow a template matching framework to obtain gridded correspondences. A log gradient that effectively handles noise in dark areas while resisting speckle noise is developed. A histogram of oriented log gradient (HOLG) is designed based on a simplified histogram of oriented gradient structure to weaken the effects of striped radiation noise. Moreover, a selective correlation strategy is designed, and a similarity metric named HOLGSC is proposed based on the selective correlation of the HOLG descriptors to overcome the effects of the unstable geometric structures of shadows and trees. Finally, after removing outliers from the matching results, we introduce the as-projective-as possible transformation model to establish geometric correspondences. We obtain several UAV SAR images and compose nine multi-view UAV SAR image pairs for experiments. The experimental results confirm that the proposed algorithm is effective and outperforms the existing state-of-the-art algorithms. In addition, a preliminary stitching result of these UAV SAR images is also presented.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.jag.2024.103678
- OA Status
- gold
- Cited By
- 4
- References
- 40
- Related Works
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- OpenAlex ID
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Raw OpenAlex JSON
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https://openalex.org/W4391243005Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.jag.2024.103678Digital Object Identifier
- Title
-
Robust multi-view UAV SAR image registration based on selective correlation of log gradient descriptorWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-25Full publication date if available
- Authors
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Xin Xiong, Guowang Jin, Qing Xu, Xiangyun Liu, Quanjie ShiList of authors in order
- Landing page
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https://doi.org/10.1016/j.jag.2024.103678Publisher landing page
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1016/j.jag.2024.103678Direct OA link when available
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Artificial intelligence, Image registration, Computer vision, Geography, Image (mathematics), Correlation, Computer science, Cartography, Pattern recognition (psychology), Mathematics, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2025: 2, 2024: 2Per-year citation counts (last 5 years)
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40Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| referenced_works | https://openalex.org/W6683411478, https://openalex.org/W2030233108, https://openalex.org/W2604898748, https://openalex.org/W2559571045, https://openalex.org/W6670673637, https://openalex.org/W2898690439, https://openalex.org/W3083797568, https://openalex.org/W2994745448, https://openalex.org/W6842973494, https://openalex.org/W4289792731, https://openalex.org/W6798175217, https://openalex.org/W6803890589, https://openalex.org/W2906762613, https://openalex.org/W3041494017, https://openalex.org/W2996158895, https://openalex.org/W2948970224, https://openalex.org/W3175531063, https://openalex.org/W2135624170, https://openalex.org/W1964855131, https://openalex.org/W2091755111, https://openalex.org/W6794223644, https://openalex.org/W2140390796, https://openalex.org/W6842944170, https://openalex.org/W6787988384, https://openalex.org/W2792119716, https://openalex.org/W3128280193, https://openalex.org/W3003290123, https://openalex.org/W2965729937, https://openalex.org/W2589547048, https://openalex.org/W3110971880, https://openalex.org/W4249418251, https://openalex.org/W2614744496, https://openalex.org/W2312710269, https://openalex.org/W4294982539, https://openalex.org/W2080878340, https://openalex.org/W3177257192, https://openalex.org/W4293118125, https://openalex.org/W3159366457, https://openalex.org/W3118276404, https://openalex.org/W3210608064 |
| referenced_works_count | 40 |
| abstract_inverted_index.A | 88, 104 |
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| corresponding_author_ids | https://openalex.org/A5085036181, https://openalex.org/A5005825479 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I169689159 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/11 |
| sustainable_development_goals[0].score | 0.699999988079071 |
| sustainable_development_goals[0].display_name | Sustainable cities and communities |
| citation_normalized_percentile.value | 0.80577518 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |