Motion compensation for dynamic single-pixel imaging via optical flow in sliding windows Article Swipe
Yuxiao Wei
,
Wenbiao Xu
,
Jiangyong Mi
,
Yi-Shuai Niu
,
Huijuan Zhang
,
Yuanjin Yu
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1364/oe.569103
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1364/oe.569103
Single-pixel imaging (SPI) faces a primary challenge in dynamic scenes due to its inherently long acquisition time, which readily induces motion blur and artifacts. Compressive sampling approaches can enhance frame rates, while motion compensation approaches can reduce motion blur. However, developing an SPI scheme that simultaneously achieves high temporal resolution and effective motion artifact suppression for complex dynamic scenes remains a challenge. We propose a scheme based on sliding-window Hadamard SPI, integrating optical flow estimation for motion compensation. This scheme firstly enhances temporal resolution via sliding-window sampling, then accurately estimates scene motion using optical flow information extracted from the single-pixel data, and subsequently compensates for the motion-induced inconsistencies in single-pixel measurements. To the best of our knowledge, this is the first work to apply a motion compensation strategy that does not require prior motion and background information to SPI of complex dynamic scenes. Simulation analyses and practical hardware experimental results collectively validate the effectiveness of the proposed method under various sampling rates and sliding-window step configurations, demonstrating its capability to significantly enhance the quality and fidelity of SPI in dynamic scenes.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1364/oe.569103
- OA Status
- gold
- References
- 28
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4413229822
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4413229822Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1364/oe.569103Digital Object Identifier
- Title
-
Motion compensation for dynamic single-pixel imaging via optical flow in sliding windowsWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-08-11Full publication date if available
- Authors
-
Yuxiao Wei, Wenbiao Xu, Jiangyong Mi, Yi-Shuai Niu, Huijuan Zhang, Yuanjin YuList of authors in order
- Landing page
-
https://doi.org/10.1364/oe.569103Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1364/oe.569103Direct OA link when available
- Concepts
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Optics, Optical flow, Pixel, Compensation (psychology), Flow (mathematics), Materials science, Computer science, Physics, Computer vision, Image (mathematics), Mechanics, Psychology, PsychoanalysisTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- References (count)
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28Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.However, | 39 |
| abstract_inverted_index.achieves | 46 |
| abstract_inverted_index.analyses | 144 |
| abstract_inverted_index.artifact | 53 |
| abstract_inverted_index.enhances | 81 |
| abstract_inverted_index.fidelity | 175 |
| abstract_inverted_index.hardware | 147 |
| abstract_inverted_index.proposed | 156 |
| abstract_inverted_index.sampling | 25, 160 |
| abstract_inverted_index.strategy | 127 |
| abstract_inverted_index.temporal | 48, 82 |
| abstract_inverted_index.validate | 151 |
| abstract_inverted_index.challenge | 6 |
| abstract_inverted_index.effective | 51 |
| abstract_inverted_index.estimates | 89 |
| abstract_inverted_index.extracted | 96 |
| abstract_inverted_index.practical | 146 |
| abstract_inverted_index.sampling, | 86 |
| abstract_inverted_index.Simulation | 143 |
| abstract_inverted_index.accurately | 88 |
| abstract_inverted_index.approaches | 26, 34 |
| abstract_inverted_index.artifacts. | 23 |
| abstract_inverted_index.background | 135 |
| abstract_inverted_index.capability | 168 |
| abstract_inverted_index.challenge. | 61 |
| abstract_inverted_index.developing | 40 |
| abstract_inverted_index.estimation | 74 |
| abstract_inverted_index.inherently | 13 |
| abstract_inverted_index.knowledge, | 116 |
| abstract_inverted_index.resolution | 49, 83 |
| abstract_inverted_index.Compressive | 24 |
| abstract_inverted_index.acquisition | 15 |
| abstract_inverted_index.compensates | 103 |
| abstract_inverted_index.information | 95, 136 |
| abstract_inverted_index.integrating | 71 |
| abstract_inverted_index.suppression | 54 |
| abstract_inverted_index.Single-pixel | 0 |
| abstract_inverted_index.collectively | 150 |
| abstract_inverted_index.compensation | 33, 126 |
| abstract_inverted_index.experimental | 148 |
| abstract_inverted_index.single-pixel | 99, 109 |
| abstract_inverted_index.subsequently | 102 |
| abstract_inverted_index.compensation. | 77 |
| abstract_inverted_index.demonstrating | 166 |
| abstract_inverted_index.effectiveness | 153 |
| abstract_inverted_index.measurements. | 110 |
| abstract_inverted_index.significantly | 170 |
| abstract_inverted_index.motion-induced | 106 |
| abstract_inverted_index.simultaneously | 45 |
| abstract_inverted_index.sliding-window | 68, 85, 163 |
| abstract_inverted_index.configurations, | 165 |
| abstract_inverted_index.inconsistencies | 107 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 6 |
| citation_normalized_percentile.value | 0.26453726 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |