Estimation of the Equivalent Number of Looks in Polarimetric Synthetic Aperture Radar Imagery

Anfinsen, Stian Normann; Doulgeris, Anthony P.; Eltoft, T.

doi:10.1109/tgrs.2009.2019269

Cited by 211 publications

(201 citation statements)

References 32 publications

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“…Figure 4f shows the k parameter for the last iteration. Although this parameter may not be regarded as the Equivalent Number of Looks (ENL) [29] it is related to it, in a similar manner to the multilook filtering window size. As explained before, the proposed method employs also the polarimetric locality to avoid mixing inhomogeneous samples of the image.…”

Section: Resultsmentioning

confidence: 99%

“…However, this measure was defined for single polarization SAR data and, when employing PolSAR data, different ENL values are obtained for each polarimetric channel. Some extensions to PolSAR data were proposed and analyzed in [29] based on the matrix trace moments (TM)L T M and on the Maximum Likelihood (ML) based on the Wishart distribution Equation (4)L M L :…”

Section: Resultsmentioning

confidence: 99%

“…where tr(·) denotes the matrix trace, | · | represents the matrix determinant and Ψ (0) (·) refers to the digamma function [29]. No analytical solution has been derived forL M L in Equation (22) and, then, this equation has to be solved numerically.…”

Section: Resultsmentioning

confidence: 99%

“…As it may be seen, there are significant differences according to the distinct ENL estimators. The performance of these estimators has been studied in detail in [29], where the advantages of taking into account the full covariance matrix inL T M andL M L are discussed. Moreover, theL M L estimator is labeled as the best one in terms of variance and robustness to texture.…”

Section: Resultsmentioning

confidence: 99%

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Bilateral Distance Based Filtering for Polarimetric SAR Data

et al. 2013

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This paper introduces a non-linear Polarimetric SAR data filtering approach able to preserve the edges and small details of the data. It is based on exploiting the data locality in both, the spatial and the polarimetric domains, in order to avoid mixing heterogeneous samples of the data. A weighted average is performed over a given window favoring pixel values that are close on both domains. The filtering technique is based on a modified bilateral filtering, which is defined in terms of spatial and polarimetric distances. These distances encapsulate all the knowledge in both domains for an adaptation to the data structure. Finally, the proposed technique is employed to process a real RADARSAT-2 dataset.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Bilateral Distance Based Filtering for Polarimetric SAR Data

et al. 2013

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“…Inspired by (Lang et al 2014), in this paper, we utilize the ENL estimation method proposed in (Anfinsen, Doulgeris, and Eltoft 2009) …”

Section: Homogeneity Measurementmentioning

confidence: 99%

Superpixel Segmentation for Polsar Images With Local Iterative Clustering and Heterogeneous Statistical Model

Xiang

Zhang

et al. 2017

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Superpixel segmentation has an advantage that can well preserve the target shape and details. In this research, an adaptive polarimetric SLIC (Pol-ASLIC) superpixel segmentation method is proposed. First, the spherically invariant random vector (SIRV) product model is adopted to estimate the normalized covariance matrix and texture for each pixel. A new edge detector is then utilized to extract PolSAR image edges for the initialization of central seeds. In the local iterative clustering, multiple cues including polarimetric, texture, and spatial information are considered to define the similarity measure. Moreover, a polarimetric homogeneity measurement is used to automatically determine the tradeoff factor, which can vary from homogeneous areas to heterogeneous areas. Finally, the SLIC superpixel segmentation scheme is applied to the airborne Experimental SAR and PiSAR L-band PolSAR data to demonstrate the effectiveness of this proposed segmentation approach. This proposed algorithm produces compact superpixels which can well adhere to image boundaries in both natural and urban areas. The detail information in heterogeneous areas can be well preserved.

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Estimation of Snow Cover Area Using Microwave SAR Dataset

Sayyad¹,

Shaikh²

2021

Climate Impacts on Sustainable Natural Resource Management

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Estimation of the Equivalent Number of Looks in Polarimetric Synthetic Aperture Radar Imagery

Cited by 211 publications

References 32 publications

Bilateral Distance Based Filtering for Polarimetric SAR Data

Bilateral Distance Based Filtering for Polarimetric SAR Data

Superpixel Segmentation for Polsar Images With Local Iterative Clustering and Heterogeneous Statistical Model

Estimation of Snow Cover Area Using Microwave SAR Dataset

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