Ultrafast spatial phase unwrapping algorithm with accurately correcting transient phase error

2021 ◽  
Author(s):  
Haitao Wu ◽  
Yiping Cao ◽  
Haihua An ◽  
Cai Xu ◽  
Hongmei Li
Keyword(s):  
Phase Error ◽  
Phase Unwrapping ◽  
Transient Phase ◽  
Spatial Phase

scholarly journals 3D Measurement of Human Chest and Abdomen Surface Based on 3D Fourier Transform and Time Phase Unwrapping

Sensors ◽  
2020 ◽  
Vol 20 (4) ◽  
pp. 1091 ◽  
Author(s):  
Haibin Wu ◽  
Shuang Yu ◽  
Xiaoyang Yu
Keyword(s):  
Fourier Transform ◽  
Phase Error ◽  
Three Dimensional ◽  
Image Sequences ◽  
Current Approach ◽  
Individual Characteristics ◽  
Phase Unwrapping ◽  
3D Measurement ◽  
Human Experiments ◽  
The Difference

Monitoring respiratory movements is an effective way to improve radiotherapy treatments of thoracic and abdominal tumors, but the current approach is limited to measuring specific points in the chest and abdomen. In this paper, a dynamic three-dimensional (3D) measurement approach of the human chest and abdomen surface is proposed, which can infer tumor movement more accurately, so the radiotherapy damage to the human body can be reduced. Firstly, color stripe patterns in the RGB color model are projected, then after color correction, the collected stripe image sequences are separated into the three RGB primary color stripe image sequences. Secondly, a fringe projection approach is used to extract the folded phase combined 3D Fourier transform with 3D Gaussian filtering. By the relationship between adjacent fringe images in the time sequence, Gaussian filter parameters with individual characteristics are designed and optimized to improve the accuracy of wrapped phase extraction. In addition, based on the difference between the fractional parts of the folded phase error, one remainder equation can be determined, which is used for time-phase unwrapping. The simulation model and human experiments show that the proposed approach can obtain the 3D image sequences of the chest and abdomen surface in respiratory motion effectively and accurately with strong anti-interference ability.

Robust Spatial Phase Unwrapping for On-Line MR-Temperature Monitoring

2007 ◽  
Author(s):  
B. Denis de Senneville ◽  
G. Maclair ◽  
M. Ries ◽  
P. Desbarats ◽  
B. Quesson ◽  
...  
Keyword(s):  
Phase Unwrapping ◽  
Temperature Monitoring ◽  
Spatial Phase ◽  
On Line

Matched spatial-phase-shifting for the temporal-phase-unwrapping in electronic speckle pattern interferometry

Optik ◽  
2001 ◽  
Vol 112 (11) ◽  
pp. 515-520 ◽  
Author(s):  
R.A. Martínez-Celorio ◽  
A. Dávila ◽  
B. Barrientos ◽  
J.H. Puga ◽  
Luis Martí López
Keyword(s):  
Speckle Pattern ◽  
Phase Unwrapping ◽  
Phase Shifting ◽  
Electronic Speckle Pattern Interferometry ◽  
Spatial Phase ◽  
Temporal Phase

scholarly journals Multi-anchor spatial phase unwrapping for fringe projection profilometry

2019 ◽  
Vol 27 (23) ◽  
pp. 33488 ◽  
Author(s):  
Sen Xiang ◽  
You Yang ◽  
Huiping Deng ◽  
Jin Wu ◽  
Li Yu
Keyword(s):  
Phase Unwrapping ◽  
Fringe Projection ◽  
Spatial Phase ◽  
Fringe Projection Profilometry

Extended Kalman Filter Phase Unwrapping Smooth Algorithm in InSAR Image

2014 ◽  
Vol 701-702 ◽  
pp. 449-452
Author(s):  
Man Yan ◽  
Li Fen Wang
Keyword(s):  
Kalman Filter ◽  
Extended Kalman Filter ◽  
Least Squares Method ◽  
Phase Error ◽  
Phase Unwrapping ◽  
Filter Method ◽  
Differential Interferometry ◽  
Key Technologies ◽  
Kalman Filter Method ◽  
Range Error

InSAR phase unwrapping is one of the key technologies in precise differential interferometry measurement. However, when the noise is more, wrapped phase easily make the unwrapping result’s errors more. To solve this problem, phase error is compensated, and extended Kalman filter gain is limited within a certain range, error is suppressed in a relatively small area. Finally, extended Kalman filter smooth reduce the errors’ spread. Using interference data of ESA ERS-1 satellite to do experiments, it show that this method is superior to least squares method, quality guided method and original Kalman filter method in unwrapping precision and quality, it has higher stability.

scholarly journals One-Step Three-Dimensional Phase Unwrapping Approach Based on Small Baseline Subset Interferograms

2020 ◽  
Vol 12 (9) ◽  
pp. 1473 ◽  
Author(s):  
Christina Esch ◽  
Joël Köhler ◽  
Karlheinz Gutjahr ◽  
Wolf-Dieter Schuh
Keyword(s):  
Spatial Information ◽  
Real Data ◽  
Single Step ◽  
Phase Unwrapping ◽  
Motion Model ◽  
Phase Gradient ◽  
Spatial Phase ◽  
Small Baseline Subset ◽  
Temporal And Spatial ◽  
Small Baseline

One of the most critical steps in a multitemporal D-InSAR analysis is the resolution of the phase ambiguities in the context of phase unwrapping. The Extended Minimum Cost Flow approach is one of the potential phase unwrapping algorithms used in the Small Baseline Subset analysis. In a first step, each phase gradient is unwrapped in time using a linear motion model and, in a second step, the spatial phase unwrapping is individually performed for each interferogram. Exploiting the temporal and spatial information is a proven method, but the two-step procedure is not optimal. In this paper, a method is presented which solves both the temporal and spatial phase unwrapping in one single step. This requires some modifications regarding the estimation of the motion model and the choice of the weights. Furthermore, the problem of temporal inconsistency of the data, which occurs with spatially filtered interferograms, must be considered. For this purpose, so called slack variables are inserted. To verify the method, both simulated and real data are used. The test region is the Lower-Rhine-Embayment in the southwest of North Rhine-Westphalia, a very rural region with noisy data. The studies show that the new approach leads to more consistent results, so that the deformation time series of the analyzed pixels can be improved.

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