High-Quality Pixel Selection Applied for Natural Scenes in GB-SAR Interferometry

Phase analysis based on high-quality pixel (HQP) is crucial to ensure the measurement accuracy of ground-based SAR (GB-SAR). The amplitude dispersion (ADI) criterion has been widely applied to identify pixels with high amplitude stability, i.e., permanent scatterers (PSs), which typically are point-wise scatterers such as stones or man-made structures. However, the PS number in natural scenes is few and limits the GB-SAR applications. This paper proposes an improved method to take HQP selection applied for natural scenes in GB-SAR interferometry. In order to increase the spatial density of HQP for phase measurement, three types of HQPs including PS, quasi-permanent scatter (QPS), and distributed scatter (DS), are selected with different criteria. The ADI method is firstly utilized to take PS selection. To select those pixels with high phase stability but moderate amplitude stability, the temporal phase coherence (TPC) is defined. Those pixels with moderate ADI values and high TPC are selected as QPSs. Then the feasibility of the DS technique is explored. To validate the feasibility of the proposed method, 2370 GB-SAR images of a natural slope are processed. Experimental results prove that the HQP number could be significantly increased while slightly sacrificing phase quality.

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High-quality pixel selection in ground-based SAR interferometry based on pseudo- and quasi-permanent scatterers analyses

Journal of Applied Remote Sensing ◽

10.1117/1.jrs.13.014507 ◽

2019 ◽

Vol 13 (01) ◽

pp. 1 ◽

Cited By ~ 1

Author(s):

Zengshu Huang ◽

Jinping Sun ◽

Qing Li ◽

Weixian Tan ◽

Pingping Huang ◽

...

Keyword(s):

Sar Interferometry ◽

High Quality ◽

Permanent Scatterers

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Transparent Object Shape Measurement Based on Deflectometry

Proceedings ◽

10.3390/icem18-05428 ◽

2018 ◽

Vol 2 (8) ◽

pp. 548

Author(s):

Zhichao Hao ◽

Yuankun Liu

Keyword(s):

Data Acquisition ◽

Phase Measurement ◽

Focal Length ◽

Three Dimensional ◽

Normal Direction ◽

Calibration Data ◽

Actual Measurement ◽

Temporal Phase ◽

Convex Lens ◽

Normal Orientation

This paper proposes a method for obtaining surface normal orientation and 3-D shape of plano-convex lens using refraction stereo. We show that two viewpoints are sufficient to solve this problem under the condition that the refractive index of the object is known. What we need to know is that (1) an accurate function that maps each pixel to the refraction point caused by the refraction of the object. (2) light is refracted only once. In the simulation, the actual measurement process is simplified: light is refracted only once; and the accurate one-to-one correspondence between incident ray and refractive ray is realized by known object points. The deformed grating caused by refraction point is also constructed in the process of simulation. A plano-convex lens with a focal length of 242.8571 mm is used for stereo data acquisition, normal direction acquisition, and the judgment of normal direction consistency. Finally, restoring the three-dimensional information of the plano-convex lens by computer simulation. Simulation results suggest that our method is feasibility. In the actual experiment, considering the case of light is refracted more than once, combining the calibration data acquisition based on phase measurement, phase-shifting and temporal phase-unwrapping techniques to complete (1) calibrating the corresponding position relationship between the monitor and the camera (2) matching incident ray and refractive ray.

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RFI Artefacts Detection in Sentinel-1 Level-1 SLC Data Based On Image Processing Techniques

Sensors ◽

10.3390/s20102919 ◽

2020 ◽

Vol 20 (10) ◽

pp. 2919 ◽

Cited By ~ 2

Author(s):

Agnieszka Chojka ◽

Piotr Artiemjew ◽

Jacek Rapiński

Keyword(s):

Image Processing ◽

Synthetic Aperture Radar ◽

Nearest Neighbor ◽

Synthetic Aperture ◽

Interferometric Synthetic Aperture Radar ◽

Sar Images ◽

Permanent Scatterers ◽

Level 1 ◽

Processing Techniques ◽

Aperture Radar

Interferometric Synthetic Aperture Radar (InSAR) data are often contaminated by Radio-Frequency Interference (RFI) artefacts that make processing them more challenging. Therefore, easy to implement techniques for artefacts recognition have the potential to support the automatic Permanent Scatterers InSAR (PSInSAR) processing workflow during which faulty input data can lead to misinterpretation of the final outcomes. To address this issue, an efficient methodology was developed to mark images with RFI artefacts and as a consequence remove them from the stack of Synthetic Aperture Radar (SAR) images required in the PSInSAR processing workflow to calculate the ground displacements. Techniques presented in this paper for the purpose of RFI detection are based on image processing methods with the use of feature extraction involving pixel convolution, thresholding and nearest neighbor structure filtering. As the reference classifier, a convolutional neural network was used.

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Ein passiv arbeitender Multi- Abstands-Sensor nach dem Prinzip der Pupillenteilung und temporärer Phasenmessung/ Α Passiv Multi-Channel 3D Range Sensor Using the Pupil Division and Temporal Phase Measurement Method

tm - Technisches Messen ◽

10.1524/teme.1998.65.78.260 ◽

1998 ◽

Vol 65 (7-8) ◽

Author(s):

Μ. Seib ◽

R. Schäfer ◽

N. Lauinger

Keyword(s):

Measurement Method ◽

Phase Measurement ◽

Range Sensor ◽

Temporal Phase

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Monitoring Three Gorge Area Landslide currently movement by Mutilplatform SAR Interferometry

10.5194/egusphere-egu2020-5334 ◽

2020 ◽

Author(s):

Tao Li ◽

Yangmao Wen ◽

Lulu Chen ◽

Jinge Wang

Keyword(s):

High Resolution ◽

Surface Deformation ◽

Test Site ◽

Deformation Monitoring ◽

Sar Interferometry ◽

Sar Image ◽

Landslide Area ◽

Sar Images ◽

The Past ◽

Huangtupo Landslide

Three Gorge area landslide hazards developed very fast after the Dam started to impound the water since 2007. There were lots of research literatures concentrated on the Badong Huangtupo Landslide area for the whole city center had to change its position in 2009. Several literatures used Envisat SAR images time series to monitoring the surface deformation from 2008~2010. The results showed good consistent with the water level changes and precipitation. &#160;The high resolution TerraSAR Spotlight images had been used to monitoring the Shuping landslide and Fanjiaping landslide area in Zigui country from 2009~2012,the InSAR results showed good details of the landslide boundary and deformation rate with DInSAR technology.This paper studies several landslide area in the Three Gorge by InSAR technology in the past few years, such as Huangtupo, Huanglashi , Daping and &#160;Baiheping landslide area , etc. al . The high resolution SAR images covered Badong and Wushan area have been collected, including the Sentinel-1, TerraSAR, RadarSAT-2, ALOS-2 SAR images. The high resolution topography in those landslide area have been collected both by UAV lidar and high resolution topography map.The Huangtupo landslide area changed a lot in the past 3 years with the buildings ruins cleared and red soil covered by the local government. The time series results by Sentinel data in this area shows the big changes but could not derive reasonable deformation results.Three Gorges Research Center for Geo-hazards (TGRC) of China University of Geosciences(CUG) built the Badong field test site in Huangtupo landslide area. This test site is composed with a tunnel group and a series of monitoring system including the inside sensors, surface deformation monitoring sensors and so on. In this paper, we mounted several new designed dihedral corner reflectors on the Huangtupo landslide area for high precision deformation monitoring by InSAR. Both the &#160;ascending and the &#160;descending orbit data of RadarSAT-2 high resolution SAR image &#160;and TerraSAR Spotlight images have been collected in this field.The preliminary results from those new acquiring SAR data series show that the traditional landslide area such as Huanglashi , Daping, Baiheping are all moving slowly with good coherence in SAR image series. &#160;The poor vegetation coverage in those landslide area helped to get the credible &#160;InSAR results. The high resolution DEM is the critical elements for the DInSAR techniques in those landslide area. The steep&#160; topography in those landslide area distorted the SAR images correspondingly.Our results shows that it is possible to use ascending and descending high resolution SAR images to monitor the landslide area with mm level precision, while the vegetation is not so dense. High resolution SAR interferometry helped a lot for the landslide boundary detection and detailed analysis. The lower resolution SAR images such as Sentinel-1 still could provide some deformation results in landslide area, but it need more auxiliary data to interpret the results.

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