A comparison of change detection statistics in POLSAR images

Kersten, P.R.; Lee, J.S.; Ainsworth, T.L.

doi:10.1109/igarss.2005.1526756

Cited by 24 publications

(26 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The seminal work on test statistics for change detection in multilook PolSAR images was done by Conradsen et al, who proposed a generalized likelihood ratio test (LRT) for equality of two complex covariance matrices and gave the asymptotic sampling distribution for the test statistic [14]. This method, also known as the Bartlett test, was compared by Kersten et al to the alternative contrast ratio and ellipticity tests [15]. Erten et al presented a new coherent similarity measure for multitemporal multichannel SAR images by means of mutual information [16].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Polarimetric SAR Change Detection With the Complex Hotelling–Lawley Trace Statistic

Akbari

Anfinsen

Doulgeris

et al. 2016

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

Abstract-In this paper, we propose a new test statistic for unsupervised change detection in polarimetric radar images. We work with multilook complex covariance matrix data, whose underlying model is assumed to be the scaled complex Wishart distribution. We use the complex-kind Hotelling-Lawley trace statistic for measuring the similarity of two covariance matrices. The distribution of the Hotelling-Lawley trace statistic is approximated by a Fisher-Snedecor distribution, which is used to define the significance level of a false alarm rate regulated change detector. Experiments on simulated and real PolSAR data sets demonstrate that the proposed change detection method gives detections rates and error rates that are comparable with the generalized likelihood ratio test.

show abstract

Section: Introductionmentioning

confidence: 99%

“…The location parameter µ of the FS distribution is computed analytically from (15). To match the second and third-order moments and retrieve the shape parameters ξ and ζ, we use minimum distance optimization [45] to solve…”

Section: Sampling Distribution Of the Hlt Statisticmentioning

confidence: 99%

Polarimetric SAR Change Detection With the Complex Hotelling–Lawley Trace Statistic

Akbari

Anfinsen

Doulgeris

et al. 2016

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

show abstract

“…T= ⋅median |w 3 − median w 3 | /c 0 (6) with being the coefficients of the diagonal subband of the Haar wavelet of the input x obtained at the first resolution scale, c 0 =0.6745 [17] [18]. The parameter introduces a smoothing factor depending on the noise level still present in the input.…”

Section: Mca With Polarimetric Data Setsmentioning

confidence: 99%

“…The approach described in [5], introduces the log-likelihood test assuming that the coherence matrices follow a complex Wishart distribution, showing a good detection performance in forested areas. The work presented in [6] introduces an inter-comparison of diverse statistical-and non-statistical-based approaches to extract changes from polarimetric data sets using simulated scenarios. The authors concluded that the assumption of the probability distribution function impacts the performance of the change detector, introducing a more difficult characterization of their detection capabilities.…”

Section: Introductionmentioning

confidence: 99%

Fully polarimetric high-resolution airborne SAR image change detection with morphological component analysis

Domínguez¹,

Henke²,

Small³

et al. 2015

SPIE Proceedings

View full text Add to dashboard Cite

Change detection for high resolution Synthetic Aperture Radar (SAR) imagery requires advanced denoising mechanisms to preserve details and minimize speckle. In this work, we propose a change detector based on a Morphological Component Analysis (MCA) of the scattering mechanisms provided with fully polarimetric data sets. With MCA, the power of each scattering mechanism is decomposed into diverse image features. By introducing a priori knowledge of the content of the scenes, and exploiting both the scattering mechanisms and their corresponding shapes, we can significantly improve performance, with fewer false alarms introduced by clutter, focusing errors, and inconsistent acquisition geometries. ABSTRACTChange detection for high resolution Synthetic Aperture Radar (SAR) imagery requires advanced denoising mechanisms to preserve details and minimize speckle. In this work, we propose a change detector based on a Morphological Component Analysis (MCA) of the scattering mechanisms provided with fully polarimetric data sets. With MCA, the power of each scattering mechanism is decomposed into diverse image features. By introducing a priori knowledge of the content of the scenes, and exploiting both the scattering mechanisms and their corresponding shapes, we can significantly improve performance, with fewer false alarms introduced by clutter, focusing errors, and inconsistent acquisition geometries.

show abstract

“…In particular, temporal multichannel change detection techniques are interesting considering their inherent properties which are independent of SAR imaging mode, such as the generalized variance ratio [7] and the maximum-likelihood ratio test (MLRT) [5], [8], [9]. In the case of comparing the variabilities of two multivariate populations, a natural measure is the ratio of their generalized variances: For temporal single-channel images, it is the ratio of their intensities, and for temporal multichannel images, it is the ratio of determinants of covariance matrices of polarimetric SAR (PolSAR) images.…”

mentioning

confidence: 99%

A New Coherent Similarity Measure for Temporal Multichannel Scene Characterization

Erten¹,

Reigber

Ferro-Famil

et al. 2012

IEEE Trans. Geosci. Remote Sensing

View full text Add to dashboard Cite

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.

show abstract

A comparison of change detection statistics in POLSAR images

Cited by 24 publications

References 10 publications

Polarimetric SAR Change Detection With the Complex Hotelling–Lawley Trace Statistic

Polarimetric SAR Change Detection With the Complex Hotelling–Lawley Trace Statistic

Fully polarimetric high-resolution airborne SAR image change detection with morphological component analysis

A New Coherent Similarity Measure for Temporal Multichannel Scene Characterization

Contact Info

Product

Resources

About