An Adaptive Spatial Filtering Algorithm Based On Nonlocal Mean Filtering For GNSS-based InSAR

Shang, Runze; Liu, Feifeng; Wang, Zhanze; Gao, Jian; Zhou, Jingtian; Yao, Di

doi:10.1109/icspcc55723.2022.9984386

Search citation statements

Order By: Relevance

Paper Sections

Select...

Interferometry and Flat-earth Phase Removal1

Introduction1

Citation Types

Supporting

Mentioning

Contrasting

Year Published

2024

Publication Types

Select...

Article2

Relationship

Self Cite0

Independent2

Authors

Journals

Cited by 2 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The interferometric phase attributed to the flat-earth reference plane is [50], which is subtracted from the phase of I[u, v] in (17) to obtain…”

Section: Interferometry and Flat-earth Phase Removalmentioning

confidence: 99%

See 1 more Smart Citation

An On-Site InSAR Terrain Imaging Method with Unmanned Aerial Vehicles

Chuang,

Kiang

2024

Sensors

View full text Add to dashboard Cite

An on-site InSAR imaging method carried out with unmanned aerial vehicles (UAVs) is proposed to monitor terrain changes with high spatial resolution, short revisit time, and high flexibility. To survey and explore a specific area of interest in real time, a combination of a least-square phase unwrapping technique and a mean filter for removing speckles is effective in reconstructing the terrain profile. The proposed method is validated by simulations on three scenarios scaled down from the high-resolution digital elevation models of the US geological survey (USGS) 3D elevation program (3DEP) datasets. The efficacy of the proposed method and the efficiency in CPU time are validated by comparing with several state-of-the-art techniques.

show abstract

“…The interferometric phase attributed to the flat-earth reference plane is [50], which is subtracted from the phase of I[u, v] in (17) to obtain…”

Section: Interferometry and Flat-earth Phase Removalmentioning

confidence: 99%

“…In [17], a 3D space-time nonlocal mean filter (NLMF) was applied to detect terrain changes by extracting nonlocal information from pixels in SAR images acquired in different time windows. In [18], a nonlocal mean filter was applied to a few persistent scattering points in a search area to improve the accuracy of 3D deformation profile.…”

Section: Introductionmentioning

confidence: 99%