A Wavelet-Based Multitemporal DInSAR Algorithm for Monitoring Ground Surface Motion

Shirzaei, M.

doi:10.1109/lgrs.2012.2208935

Cited by 62 publications

(97 citation statements)

References 14 publications

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“…In [20], [21] methods for deblocking artifact of image were developed by using the wavelet for solving the drawbacks in [10]- [14]. The method of [20] applies a variety of waveletbased multitemporal DInSAR algorithms to remove artifacts, such as spatially correlated and temporally uncorrelated components, the digital elevation model, and orbital errors of an image.…”

Section: Deblocking Artifactmentioning

confidence: 99%

“…The method of [20] applies a variety of waveletbased multitemporal DInSAR algorithms to remove artifacts, such as spatially correlated and temporally uncorrelated components, the digital elevation model, and orbital errors of an image. However, in various images which have low bit rates, the method of [20] often removes some part of undistorted satellite image, like texture area and flat area that are assumed as distorted images. The method of [21] also can remove blocking artifacts by using orthogonal projections of wavelets from an upside down pyramid-shaped region in a multi-dimensional space.…”

Section: Deblocking Artifactmentioning

confidence: 99%

“…Thus, removing blocking artifact has been left problem for linear filtering [20]- [22], [24]- [31] in satellite image processing analysis. The linear filter methods [20]- [22], [24]- [31] give blurring effect in edges and other fine satellite image details.…”

Section: Deblocking Artifactmentioning

confidence: 99%

“…The linear filter methods [20]- [22], [24]- [31] give blurring effect in edges and other fine satellite image details. It is difficult for image analysis of linear filter to reconstruct an undistorted image from a distorted image.…”

Section: Deblocking Artifactmentioning

confidence: 99%

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Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

Risnandar

Aritsugi

2018

IEICE Trans. Inf. & Syst.

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SUMMARYNew deblocking artifact, or blocking artifact reduction, algorithms based on nonlinear adaptive soft-threshold anisotropic filter in wavelet are proposed. Our deblocking algorithm uses soft-threshold, adaptive wavelet direction, adaptive anisotropic filter, and estimation. The novelties of this paper are an adaptive soft-threshold for deblocking artifact and an optimal intersection of confidence intervals (OICI) method in deblocking artifact estimation. The soft-threshold values are adaptable to different thresholds of flat area, texture area, and blocking artifact. The OICI is a reconstruction technique of estimated deblocking artifact which improves acceptable quality level of estimated deblocking artifact and reduces execution time of deblocking artifact estimation compared to the other methods. Our adaptive OICI method outperforms other adaptive deblocking artifact methods. Our estimated deblocking artifact algorithms have up to 98% of MSE improvement, up to 89% of RMSE improvement, and up to 99% of MAE improvement. We also got up to 77.98% reduction of computational time of deblocking artifact estimations, compared to other methods. We have estimated shift and add algorithms by using Euler + +(E + +) and Runge-Kutta of order 4++ (RK4 + +) algorithms which iterate one step an ordinary differential equation integration method. Experimental results showed that our E + + and RK4 + + algorithms could reduce computational time in terms of shift and add, and RK4 + + algorithm is superior to E + + algorithm.

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Section: Deblocking Artifactmentioning

confidence: 99%

Section: Deblocking Artifactmentioning

confidence: 99%

Section: Deblocking Artifactmentioning

confidence: 99%

Section: Deblocking Artifactmentioning

confidence: 99%

See 2 more Smart Citations

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

Risnandar

Aritsugi

2018

IEICE Trans. Inf. & Syst.

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“…Ignoring this covariance will bias the inversion procedure. A potential solution is to perform the time series analysis in the wavelet domain in which wavelets are considered independent [Hetland et al, 2012;Shirzaei , 2013]. However, this assumption still remains an approximation.…”

Section: Introductionmentioning

confidence: 99%

A Multipixel Time Series Analysis Method Accounting for Ground Motion, Atmospheric Noise, and Orbital Errors

Jolivet

Simons

2018

Geophysical Research Letters

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Interferometric synthetic aperture radar time series methods aim to reconstruct time‐dependent ground displacements over large areas from sets of interferograms in order to detect transient, periodic, or small‐amplitude deformation. Because of computational limitations, most existing methods consider each pixel independently, ignoring important spatial covariances between observations. We describe a framework to reconstruct time series of ground deformation while considering all pixels simultaneously, allowing us to account for spatial covariances, imprecise orbits, and residual atmospheric perturbations. We describe spatial covariances by an exponential decay function dependent of pixel‐to‐pixel distance. We approximate the impact of imprecise orbit information and residual long‐wavelength atmosphere as a low‐order polynomial function. Tests on synthetic data illustrate the importance of incorporating full covariances between pixels in order to avoid biased parameter reconstruction. An example of application to the northern Chilean subduction zone highlights the potential of this method.

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A seamless multitrack multitemporal InSAR algorithm

Shirzaei

2015

Geochem Geophys Geosyst

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The zones of overlap between adjacent Synthetic Aperture Radar (SAR) satellite tracks are illuminated twice more frequently than elsewhere in the SAR scene. Here, an alternative approach is presented to combine the overlapping segments of SAR images acquired at adjacent tracks and generate accurate and high spatiotemporal resolution map of the surface deformation field. To this end, a new approach is developed to unify the datums. Effects due to the difference in look angle between two overlapping tracks and atmospheric delay are estimated and removed using Kalman and wavelet-based filters. This approach is first tested at Hawaii Island, where tracks 200 and 429 of Envisat C-band satellite overlap over the Kilauea south flank. The obtained time series improves the temporal sampling rate by a factor of two and comparison with GPS time series demonstrates that the presented method accurately measures the nonlinear deformation field. The advantages of this method are further demonstrated by combining SAR data sets acquired by Envisat C-band and ALOS L-band satellites over the San Francisco Bay Area, California. The validation test shows that the seamless combination of C-band and L-band time series accurately measures the surface deformation at higher resolution.

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A Wavelet-Based Multitemporal DInSAR Algorithm for Monitoring Ground Surface Motion

Cited by 62 publications

References 14 publications

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

Deblocking Artifact of Satellite Image Based on Adaptive Soft-Threshold Anisotropic Filter Using Wavelet

A Multipixel Time Series Analysis Method Accounting for Ground Motion, Atmospheric Noise, and Orbital Errors

A seamless multitrack multitemporal InSAR algorithm

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