View in EDS HTML Full Text PDF Full Text

ICESat-2 Water Photon Denoising and Water Level Extraction Method Combining Elevation Difference Exponential Attenuation Model with Hough Transform.

Saved in:
Bibliographic Details
Title: ICESat-2 Water Photon Denoising and Water Level Extraction Method Combining Elevation Difference Exponential Attenuation Model with Hough Transform.
Authors: Ju, Xilai1 (AUTHOR), Li, Yongjian2 (AUTHOR), Ji, Song2,3 (AUTHOR), Gong, Danchao3,4 (AUTHOR), Liu, Hao4,5 (AUTHOR), Yan, Zhen1,2 (AUTHOR), Liu, Xining2,5 (AUTHOR) liuxining@mail.cgs.gov.cn, Niu, Hao3,5 (AUTHOR)
Source: Remote Sensing. Aug2025, Vol. 17 Issue 16, p2885. 25p.
Subjects: Water levels, Hough transforms, Water quality monitoring, Image processing, Signal denoising, Curve fitting, Statistical models
Abstract: For addressing the technical challenges of photon denoising and water level extraction in ICESat-2 satellite-based water monitoring applications, this paper proposes an innovative solution integrating Gaussian function fitting with Hough transform. The method first employs histogram Gaussian fitting to achieve coarse denoising of water body regions. Subsequently, a probability attenuation model based on elevation differences between adjacent photons is constructed to accomplish refined denoising through iterative optimization of adaptive thresholds. Building upon this foundation, the Hough transform technique from image processing is introduced into photon cloud processing, enabling robust water level extraction from ICESat-2 data. Through rasterization, discrete photon distributions are converted into image space, where straight lines conforming to the photon distribution are then mapped as intersection points of sinusoidal curves in Hough space. Leveraging the noise-resistant characteristics of the Hough space accumulator, the interference from residual noise photons is effectively eliminated, thereby achieving high-precision water level line extraction. Experiments were conducted across five typical water bodies (Qinghai Lake, Long Land, Ganquan Island, Qilian Yu Islands, and Miyun Reservoir). The results demonstrate that the proposed denoising method outperforms DBSCAN and OPTICS algorithms in terms of accuracy, precision, recall, F1-score, and computational efficiency. In water level estimation, the absolute error of the Hough transform-based line detection method remains below 2 cm, significantly surpassing the performance of mean value, median value, and RANSAC algorithms. This study provides a novel technical framework for effective global water level monitoring. [ABSTRACT FROM AUTHOR]
Copyright of Remote Sensing is the property of MDPI 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.)
Database: Engineering Source
Full text is not displayed to guests.
FullText Links:
  – Type: pdflink
Text:
  Availability: 1
Header DbId: egs
DbLabel: Engineering Source
An: 187613871
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: ICESat-2 Water Photon Denoising and Water Level Extraction Method Combining Elevation Difference Exponential Attenuation Model with Hough Transform.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Ju%2C+Xilai%22">Ju, Xilai</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Li%2C+Yongjian%22">Li, Yongjian</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Ji%2C+Song%22">Ji, Song</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Gong%2C+Danchao%22">Gong, Danchao</searchLink><relatesTo>3,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Hao%22">Liu, Hao</searchLink><relatesTo>4,5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yan%2C+Zhen%22">Yan, Zhen</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Xining%22">Liu, Xining</searchLink><relatesTo>2,5</relatesTo> (AUTHOR)<i> liuxining@mail.cgs.gov.cn</i><br /><searchLink fieldCode="AR" term="%22Niu%2C+Hao%22">Niu, Hao</searchLink><relatesTo>3,5</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Aug2025, Vol. 17 Issue 16, p2885. 25p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Water+levels%22">Water levels</searchLink><br /><searchLink fieldCode="DE" term="%22Hough+transforms%22">Hough transforms</searchLink><br /><searchLink fieldCode="DE" term="%22Water+quality+monitoring%22">Water quality monitoring</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Signal+denoising%22">Signal denoising</searchLink><br /><searchLink fieldCode="DE" term="%22Curve+fitting%22">Curve fitting</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: For addressing the technical challenges of photon denoising and water level extraction in ICESat-2 satellite-based water monitoring applications, this paper proposes an innovative solution integrating Gaussian function fitting with Hough transform. The method first employs histogram Gaussian fitting to achieve coarse denoising of water body regions. Subsequently, a probability attenuation model based on elevation differences between adjacent photons is constructed to accomplish refined denoising through iterative optimization of adaptive thresholds. Building upon this foundation, the Hough transform technique from image processing is introduced into photon cloud processing, enabling robust water level extraction from ICESat-2 data. Through rasterization, discrete photon distributions are converted into image space, where straight lines conforming to the photon distribution are then mapped as intersection points of sinusoidal curves in Hough space. Leveraging the noise-resistant characteristics of the Hough space accumulator, the interference from residual noise photons is effectively eliminated, thereby achieving high-precision water level line extraction. Experiments were conducted across five typical water bodies (Qinghai Lake, Long Land, Ganquan Island, Qilian Yu Islands, and Miyun Reservoir). The results demonstrate that the proposed denoising method outperforms DBSCAN and OPTICS algorithms in terms of accuracy, precision, recall, F1-score, and computational efficiency. In water level estimation, the absolute error of the Hough transform-based line detection method remains below 2 cm, significantly surpassing the performance of mean value, median value, and RANSAC algorithms. This study provides a novel technical framework for effective global water level monitoring. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Remote Sensing is the property of MDPI 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.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=187613871
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.3390/rs17162885
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 25
        StartPage: 2885
    Subjects:
      – SubjectFull: Water levels
        Type: general
      – SubjectFull: Hough transforms
        Type: general
      – SubjectFull: Water quality monitoring
        Type: general
      – SubjectFull: Image processing
        Type: general
      – SubjectFull: Signal denoising
        Type: general
      – SubjectFull: Curve fitting
        Type: general
      – SubjectFull: Statistical models
        Type: general
    Titles:
      – TitleFull: ICESat-2 Water Photon Denoising and Water Level Extraction Method Combining Elevation Difference Exponential Attenuation Model with Hough Transform.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Ju, Xilai
      – PersonEntity:
          Name:
            NameFull: Li, Yongjian
      – PersonEntity:
          Name:
            NameFull: Ji, Song
      – PersonEntity:
          Name:
            NameFull: Gong, Danchao
      – PersonEntity:
          Name:
            NameFull: Liu, Hao
      – PersonEntity:
          Name:
            NameFull: Yan, Zhen
      – PersonEntity:
          Name:
            NameFull: Liu, Xining
      – PersonEntity:
          Name:
            NameFull: Niu, Hao
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 15
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 20724292
          Numbering:
            – Type: volume
              Value: 17
            – Type: issue
              Value: 16
          Titles:
            – TitleFull: Remote Sensing
              Type: main
ResultId 1