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High-Resolution Image Processing and Spatiotemporal Data Transmission System Based on GPU Acceleration.

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Titel: High-Resolution Image Processing and Spatiotemporal Data Transmission System Based on GPU Acceleration.
Autoren: Xing, Kongduo, Li, Guozhang, Wang, Yetong, Alfred, Rayner
Quelle: International Journal of High Speed Electronics & Systems; Jun2025, Vol. 34 Issue 2, p1-17, 17p
Schlagwörter: DATA transmission systems, INFORMATION technology, CENTRAL processing units, SPATIOTEMPORAL processes, PROCESS capability
Abstract: With the development of information technology and the increasing demand for data processing, the serial mode of the central processing unit (CPU) is difficult to efficiently transmit large-scale spatiotemporal data, and the processing effect for high-resolution images is not good. This paper designed a high-resolution image processing and spatiotemporal data transmission system based on graphics processing unit (GPU) acceleration to improve the processing efficiency of large-scale spatiotemporal data. In this paper, traffic spatiotemporal data was taken as an example for analysis. Large-scale traffic image data was collected by road monitoring equipment, and image compression was performed on the collected image. Fourier transform was used to eliminate image data redundancy, and GPU-accelerated parallel processing was used to achieve fast image defogging and data transmission. This paper selected 2TB of traffic spatiotemporal data with image resolutions of 540P, 720P, 1080P, 1440P, and 2160P. GPU acceleration was performed using the Compute Unified Device Architecture (CUDA). In images with a resolution of 2160P, the processing time for CPU and GPU acceleration was 2900ms and 28ms, respectively, with an acceleration ratio of 103.6. A high-resolution image processing and spatiotemporal data transmission system based on GPU acceleration can improve the efficiency of traffic spatiotemporal data processing and have excellent concurrent processing capabilities. [ABSTRACT FROM AUTHOR]
Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: High-Resolution Image Processing and Spatiotemporal Data Transmission System Based on GPU Acceleration.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Xing%2C+Kongduo%22">Xing, Kongduo</searchLink><br /><searchLink fieldCode="AR" term="%22Li%2C+Guozhang%22">Li, Guozhang</searchLink><br /><searchLink fieldCode="AR" term="%22Wang%2C+Yetong%22">Wang, Yetong</searchLink><br /><searchLink fieldCode="AR" term="%22Alfred%2C+Rayner%22">Alfred, Rayner</searchLink>
– Name: TitleSource
  Label: Source
  Group: Src
  Data: International Journal of High Speed Electronics & Systems; Jun2025, Vol. 34 Issue 2, p1-17, 17p
– Name: Subject
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  Group: Su
  Data: <searchLink fieldCode="DE" term="%22DATA+transmission+systems%22">DATA transmission systems</searchLink><br /><searchLink fieldCode="DE" term="%22INFORMATION+technology%22">INFORMATION technology</searchLink><br /><searchLink fieldCode="DE" term="%22CENTRAL+processing+units%22">CENTRAL processing units</searchLink><br /><searchLink fieldCode="DE" term="%22SPATIOTEMPORAL+processes%22">SPATIOTEMPORAL processes</searchLink><br /><searchLink fieldCode="DE" term="%22PROCESS+capability%22">PROCESS capability</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: With the development of information technology and the increasing demand for data processing, the serial mode of the central processing unit (CPU) is difficult to efficiently transmit large-scale spatiotemporal data, and the processing effect for high-resolution images is not good. This paper designed a high-resolution image processing and spatiotemporal data transmission system based on graphics processing unit (GPU) acceleration to improve the processing efficiency of large-scale spatiotemporal data. In this paper, traffic spatiotemporal data was taken as an example for analysis. Large-scale traffic image data was collected by road monitoring equipment, and image compression was performed on the collected image. Fourier transform was used to eliminate image data redundancy, and GPU-accelerated parallel processing was used to achieve fast image defogging and data transmission. This paper selected 2TB of traffic spatiotemporal data with image resolutions of 540P, 720P, 1080P, 1440P, and 2160P. GPU acceleration was performed using the Compute Unified Device Architecture (CUDA). In images with a resolution of 2160P, the processing time for CPU and GPU acceleration was 2900ms and 28ms, respectively, with an acceleration ratio of 103.6. A high-resolution image processing and spatiotemporal data transmission system based on GPU acceleration can improve the efficiency of traffic spatiotemporal data processing and have excellent concurrent processing capabilities. [ABSTRACT FROM AUTHOR]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of High Speed Electronics & Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1142/S0129156424400056
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 17
        StartPage: 1
    Subjects:
      – SubjectFull: DATA transmission systems
        Type: general
      – SubjectFull: INFORMATION technology
        Type: general
      – SubjectFull: CENTRAL processing units
        Type: general
      – SubjectFull: SPATIOTEMPORAL processes
        Type: general
      – SubjectFull: PROCESS capability
        Type: general
    Titles:
      – TitleFull: High-Resolution Image Processing and Spatiotemporal Data Transmission System Based on GPU Acceleration.
        Type: main
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          Name:
            NameFull: Xing, Kongduo
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            NameFull: Li, Guozhang
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            NameFull: Wang, Yetong
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            NameFull: Alfred, Rayner
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          Dates:
            – D: 01
              M: 06
              Text: Jun2025
              Type: published
              Y: 2025
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              Value: 01291564
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              Value: 34
            – Type: issue
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          Titles:
            – TitleFull: International Journal of High Speed Electronics & Systems
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