A Novel Stitching Method for Dust and Rock Analysis Based on Yutu Rover Panoramic Imagery
Abstract
The distributions of lunar dust and rock can reflect a large amount of physical and geological information, which has contributed to analyze the environment of the Moon. China's Yutu rover collected large numbers of high-definition images of the lunar surface. In order to obtain a wide field of view and study the lunar environment at close quarters, this article proposes a novel image stitching method named as-least-loss-as-possible wrap to provide a reasonable wider overview of the studying area based on the Yutu rover. In the proposed scheme, a double-feature matching approach is designed to solve the matching error which is generated by the specific environment of the lunar surface. From the stitched image, it can be found that the proposed method can achieve well stitched results for scientific studies, the distribution of the lunar dust on the rock's surface associates with the shadow (temperature), roughness, and height of the rock, and a special ribbon-type distribution of the lunar rocks is demonstrated clearly in a wide stitched image. This ribbon band is caused by the density inhomogeneity of impact target. And the distribution of lunar dust on the rock has the same pattern, even on the whole Moon.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The concentration of Asian studies in 2010-2013 might be influenced by Moon landing activity.
“which might be influenced by the Moon landing activity [77,78].”
From Semantic Terrain Segmentation in the Navigation Vision of Planetary Rovers—A Systematic Literature Review (2022) · cites this paper as [78]
Chinese Moon landing (Chang'E) and lunar rover (Yutu) projects contributed to the increase of studies during 2010-2013.
“Chinese Moon landing (Chang’E [77]) and lunar rover (Yutu [78]) projects contribute to the increase of studies during this period.”
From Semantic Terrain Segmentation in the Navigation Vision of Planetary Rovers—A Systematic Literature Review (2022) · cites this paper as [78]
Cites
Speeded-Up Robust Features (SURF)
Bay, H., Ess, A., Tuytelaars, T., & Van Gool, L. (2008) · Computer Vision and Image Understanding · doi:10.1016/j.cviu.2007.09.014 · Cited by 13,557 · cited 4× · see citing works
“[29] H. Bay, A. Ess, T. Tutelaars, and L. V. Gool, “Speeded-up robust features (SURF),” Comput.”
MethodInfluential
Flagged first, then by citations
Cited by
Sorted by citations
Kuang, B., Gu, C., Rana, Z. A., Zhao, Y., Sun, S., & Nnabuife, S. G. (2022) · Sensors · doi:10.3390/s22218393 · Cited by 15 · see citing works
Sky and Ground Segmentation in the Navigation Visions of the Planetary Rovers
Kuang, B., Rana, Z. A., & Zhao, Y. (2021) · Sensors · doi:10.3390/s21216996 · Cited by 14 · see citing works
- Authors
- Ye, B., Cai, Z., Lan, T., & Cao, W.
- Affiliations
- Macau University of Science and Technology (MO)
- Chinese Academy of Sciences (CN)
- Venue
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
- Published
- 2019-11
- Volume
- 12
- Issue
- 11
- Pages
- 4457-4466
- ISSN
- 1939-1404 (ISSN-L)
- 2151-1535
- OpenAlex
- W2983576236
- Cited by
- 6
- References
- 1
- Citations by year
- 2023: 1 · 2022: 1 · 2021: 2 · 2020: 1 · 2019: 1
- FWCI
- 0.86
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (publishedVersion)
- Funders
- Science and Technology Development Fund of Macau (0012/2018/A1, 0069/2018/A2, 048/2016/A2)
- State Key Laboratory of Remote Sensing Science (OFSLRSS201901)
- State Key Laboratory of Virtual Reality Technology and Systems (VRLAB2019C02)
- Beihang University (VRLAB2019C02)
- State Key Laboratory of Computer Aided Design and Computer Graphics (A1910)
- Research and Development Fund of Beijing Institute of Technology, Zhuhai (XK-2018-04)
- Topics
- Physical Sciences › Engineering › Ocean Engineering › Satellite Image Processing and Photogrammetry
- Physical Sciences › Engineering › Media Technology › Advanced Image Fusion Techniques
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Image and Video Retrieval Techniques
- Keywords
- image stitching, Yutu rover, lunar dust, lunar rocks, panoramic images, lunar surface environment, lunar geology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review