&lt;title&gt;Filtering of layover areas in high-resolution IFSAR for building extraction&lt;/title&gt;

Petit, David; Adragna, F.; Durou, Jean‐Denis

doi:10.1117/12.410663

Cited by 7 publications

(3 citation statements)

References 2 publications

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“…Huaping Xu, Member, IEEE, Siyuan Wang, Shuo Li, Guobing Zeng, Zhenwan You, and Wei Li S application in ERS images. Petit et al [21] verified the feasibility of spectrum shift theory using simulated images to process urban SAR images. In 2016, Liu et al [22] proposed to extract the layover area of high-rise buildings by quantifying the spectral shift.…”

Section: Multi-baseline Insar Layover Detection Based On Local Frequency and Eigenvaluementioning

confidence: 98%

Multibaseline InSAR Layover Detection Based on Local Frequency and Eigenvalue

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Layover detection has long been the focus of attention for Interferometric Synthetic Aperture Radar (InSAR) data processing. As for the existing layover detection methods, most of them are applied to single-baseline scenarios. Since multi-baseline InSAR provides more image samples, the performance of layover detection can be further improved. In this paper, a joint detection method of layover is proposed on the basis of local frequency and eigenvalue of multi-baseline InSAR. To obtain a precise local frequency, maximum likelihood estimation is performed for flattened interferometric phase fusion and removing the reference terrain phase is chosen to ensure the proportionality of flattened phase to the baseline length. Adaptive image selection based on coherence is proposed to obtain a distinct eigenvalue. Then, the joint detection method is elaborated on. Based on the results of local frequency estimation and eigenvalue decomposition, precise thresholds are set for joint detection, and joint judgment is made by combining the layover detected by local frequency, the layover detected by eigenvalue and the thresholds. Finally, the proposed method is validated through comparative experiments on simulated data and real data. Both theoretical analysis and experimental results show the feasibility and superiority of the proposed method.

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Section: Multi-baseline Insar Layover Detection Based On Local Frequency and Eigenvaluementioning

confidence: 98%

Multibaseline InSAR Layover Detection Based on Local Frequency and Eigenvalue

Wang

et al. 2021

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…First analysis concerning the joint statistic of SAR images in layover areas was published by [3]. In [4], the authors utilised the spectral shift between master and slave image to distinguish vertical from horizontal signal component. More recently, in [5], edges are detected in the phase image at both layover borders, relying on a Gaussian Markov Random Fields approach.…”

Section: Introductionmentioning

confidence: 99%

Parameterisation of layover detector for urban analysis in InSAR data

Dubois

Thiele

Welte

et al. 2015

2015 Joint Urban Remote Sensing Event (JURSE)

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Building detection is an important topic in InSAR data analysis. Due to the high resolution of modern SAR systems, analysis of urban areas by interferometry is now possible. This opens the floor to new applications, considering not only magnitude images, but also phase images. For this reason, we developed a ramp detector that extracts layover areas of buildings. In this paper, we describe the parameterisation of the layover detector and describe a strategy for specifying the best-suited parameters. Finally, we show results of our parameterisation approach

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“…Combined with the advantages of very high resolution, building infrastructure information retrial with InSAR data keeps a hot topic in urban application. In 2000, Petit et al [20] exploited the spectral shift between the interferometric image pair in order to separate the vertical signal from the horizontal signal, and Gamba et al [21] proposed a method to extract and characterize the building structures from the 3D terrain elevation data, which utilized a modified machine vision approach and tested on several large buildings.…”

Section: Introductionmentioning

confidence: 99%

High-Rise Building 3D Reconstruction with the Wrapped Interferometric Phase

Guo

Wang

Zang

et al. 2019

Sensors

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The great development of high-resolution SAR system gives more opportunities to observe building structures in detail, especially the advanced interferometric SAR (InSAR), which techniques attract more attention on exploiting useful information on urban infrastructures. Considering that the high-rise buildings in urban areas are quite common in big cities, it is of great importance to retrieve the three-dimension (3D) information of the urban high-rise buildings in urban remote sensing applications. In this paper, the 3D reconstruction of high-rise buildings using the wrapped InSAR phase image was studied, referring to the geometric modulation in very high resolution (VHR) SAR images, such as serious layover cause by high-rise buildings. Under the assumption of a rectangular shape, the high-rise buildings were detected and building façades were extracted based on the local frequency analysis of the layover fringe patterns. Then 3D information of buildings were finally extracted according to the detected façade geometry. Except for testing on a small urban area from the TanDEM-X data, the experiment carried on the single-pass InSAR wrapped phase in the wide urban scene, which was collected by the Chinese airborne N-SAR system, also demonstrated the possibility and applicability of the approach.

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<title>Filtering of layover areas in high-resolution IFSAR for building extraction</title>

Cited by 7 publications

References 2 publications

Multibaseline InSAR Layover Detection Based on Local Frequency and Eigenvalue

Multibaseline InSAR Layover Detection Based on Local Frequency and Eigenvalue

Parameterisation of layover detector for urban analysis in InSAR data

High-Rise Building 3D Reconstruction with the Wrapped Interferometric Phase

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