Intensity-driven adaptive-neighborhood technique for polarimetric and interferometric SAR parameters estimation

Vasile, Gabriel; Trouvé, Emmanuël; Lee, Jong-Sen; Buzuloiu, Vasile

doi:10.1109/tgrs.2005.864142

Cited by 284 publications

(195 citation statements)

References 48 publications

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“…Compared with PSs, DSs usually maintain a low signal-to-noise-ratio (SNR) and a de-noised coherence. The approach of phase optimization in SqueeSAR™ [8] and the LBFGS (Limited memory Broyden-Fletcher-Goldfarb-Shannon) algorithm were adopted for the phase reconstruction of DS points after the procedure of an adaptive homogenous filtering [19][20][21]. The algorithm of LBFGS has similar performance in resolving nonlinear problems compared with quasi-Newton methods [22].…”

Section: Methodology and Experimental Proceduresmentioning

confidence: 99%

Monitoring Cultural Heritage Sites with Advanced Multi-Temporal InSAR Technique: The Case Study of the Summer Palace

et al. 2016

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Cultural heritage sites are rare and irreplaceable wealth of human civilization. The majority of them are becoming unstable due to a combination of human and natural disturbances. High-precision, efficient deformation monitoring facilitates the early recognition of potential risks and enables preventive diagnosis of heritage sites. In this study, an advanced Multi-Temporal Interferometric Synthetic Aperture Radar (MTInSAR) approach was developed by jointly analyzing Persistent Scatterers (PSs) and Distributed Scatterers (DSs) using high-resolution SAR images. Taking the World Heritage Site of Summer Palace in Beijing as the experimental site, deformation resulting from PSs/DSs showed that overall the site was generally stable except for specific areas and/or monuments. Urbanization (construction and demolition) triggered new subsidence in the vicinity of East and South Gate of the site. Slight to moderate (mm/cm-level) instabilities of ruins and monuments on Longevity Hill were detected, perhaps due to a combination of destructive anthropogenic activities and long-term natural decay. Subsidence was also detected along the Kunming Lakeside and was probably attributable to variation of the groundwater level, excessive visitor numbers as well as lack of maintenance. This study presents the potential of the MTInSAR approach for the monitoring and conservation of cultural heritage sites.

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Section: Methodology and Experimental Proceduresmentioning

confidence: 99%

Monitoring Cultural Heritage Sites with Advanced Multi-Temporal InSAR Technique: The Case Study of the Summer Palace

et al. 2016

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“…However, as discussed in the literature, the use of larger window sizes with fixed shapes may give unsatisfactory results, since the stationary/homogeneous assumption is often no longer valid and the accuracy of final estimates can decrease. Because of this, different covariance matrix estimation methods can be considered [29], [30]. Here, a region growing technique explained in [30] has been used instead of a fixed window size.…”

Section: A Global Analysis Of the MImentioning

confidence: 99%

“…Because of this, different covariance matrix estimation methods can be considered [29], [30]. Here, a region growing technique explained in [30] has been used instead of a fixed window size. In this method, only six intensity values from PolInSAR data are used to decide on the number of samples for maximumlikelihood covariance estimation.…”

Section: A Global Analysis Of the MImentioning

confidence: 99%

“…Then, the unknown asymptotic parameters Σ 11 , Σ 22 , and P 2 , which parameterize the pdf p(A 11 , A 22 ), can be estimated by maximum-likelihood rule as explained in the Appendix. In practice, the estimation of nonrandom variables may be relaxed: The random variables A 11 and A 22 are estimated by an initial nine-sample multilooking; then, the expectation variables can be calculated from the covariance matrices obtained by the method [30]. Here, it is worth noting that the estimated matrices by the practical technique are essentially the same as the matrices obtained directly employing the maximum-likelihood rule explained in the Appendix.…”

Section: A Global Analysis Of the MImentioning

confidence: 99%

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A New Coherent Similarity Measure for Temporal Multichannel Scene Characterization

Erten¹,

Reigber

Ferro-Famil

et al. 2012

IEEE Trans. Geosci. Remote Sensing

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Abstract-This paper proposes a new method for a measure of coherent similarity between temporal multichannel synthetic aperture radar (SAR) images and its implementation to change detection application. The method is based on mutual information (MI) from information theory. The MI measures the amount of information in common between coherent temporal multichannel SAR acquisitions. In order to develop an algorithm for all kinds of SAR images, such as interferometric SAR, polarimetric-interferometric SAR (PolInSAR), and partial PolIn-SAR, first, the joint density function of temporal multichannel images based on their second-order statistics has been derived. Then, the derived joint density function is used to calculate an analytical expression for the MI between temporal images, which is assumed to be maximal if the temporal images are identical. Although, in this paper, a new coherent similarity measure has analytically been derived for temporal polarimetric SAR images based on complex Wishart process in time, since the mathematical formulation is general, it can equally well be implemented into any kind of multivariate remote sensing data, such as multispectral optical and interferometric images after small continuation. This derived quantity has been implemented for change detection application whose aim is to characterize the temporal behavior of the acquisitions. A comparison between the proposed and the other well-known change detection methods by means of scene characterization is shown, describing the advantages due to the fact that the proposed change detector involves almost every facet of applied change detection.

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“…The refined Lee filter selected the similar pixels to reinforce homogeneity according to eight non-square windows as the templates [1,2]. Similarly, in the improved sigma filter, the two-sigma probability ranges were utilizes to select homogeneous pixels [3][4][5], and the intensity-driven adaptive-neighborhood (IDAN) was proposed by grouping pixels with similar statistical properties [6]. Furthermore, the bilateral filter calculates the weighted average based on the similarity between pixels in the local windows of …”

Section: Introductionmentioning

confidence: 99%

Feature-Based Nonlocal Polarimetric SAR Filtering

et al. 2017

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Polarimetric synthetic aperture radar (PolSAR) images are inherently contaminated by multiplicative speckle noise, which complicates the image interpretation and image analyses. To reduce the speckle effect, several adaptive speckle filters have been developed based on the weighted average of the similarity measures commonly depending on the model or probability distribution, which are often affected by the distribution parameters and modeling texture components. In this paper, a novel filtering method introduces the coefficient of variance (CV) and Pauli basis (PB) to measure the similarity, and the two features are combined with the framework of the nonlocal mean filtering. The CV is used to describe the complexity of various scenes and distinguish the scene heterogeneity; moreover, the Pauli basis is able to express the polarimetric information in PolSAR image processing. This proposed filtering combines the CV and Pauli basis to improve the estimation accuracy of the similarity weights. Then, the similarity of the features is deduced according to the test statistic. Subsequently, the filtering is proceeded by using the nonlocal weighted estimation. The performance of the proposed filter is tested with the simulated images and real PolSAR images, which are acquired by AIRSAR system and ESAR system. The qualitative and quantitative experiments indicate the validity of the proposed method by comparing with the widely-used despeckling methods.

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Intensity-driven adaptive-neighborhood technique for polarimetric and interferometric SAR parameters estimation

Cited by 284 publications

References 48 publications

Monitoring Cultural Heritage Sites with Advanced Multi-Temporal InSAR Technique: The Case Study of the Summer Palace

Monitoring Cultural Heritage Sites with Advanced Multi-Temporal InSAR Technique: The Case Study of the Summer Palace

A New Coherent Similarity Measure for Temporal Multichannel Scene Characterization

Feature-Based Nonlocal Polarimetric SAR Filtering

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