Low-Cost Robust Estimation for the Single-Look $\mathcal{G}_{I}^{0}$  Model Using the Pareto Distribution

Chan, Débora; Rey, Andrea; Gambini, Juliana; Frery, Alejandro C.

doi:10.1109/lgrs.2019.2956635

Cited by 3 publications

(2 citation statements)

References 21 publications

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“…As noted by, among others Ref. [15,Fig. 5], one should expect that extremely heterogeneous samples as, for instance, those from urban areas, are described in this region of the parameter space.…”

Section: Performance Analysismentioning

confidence: 73%

An Improved Minimum-Distance Texture Estimator for Speckled Data Under the $$\mathscr {G}^0$$ Model

Cassetti

Frery

2022

J Math Imaging Vis

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The G 0 distribution is an apt model for speckled data, such as SAR imagery, because it possesses the ability to characterize areas with different degrees of texture. In the monopolarized case, this distribution depends on three parameters: the texture, the scale, and the number of looks. The first one is related to the roughness of the image, so its estimation deserves special attention. This paper proposes and compares estimation methods of the texture parameter in intensity format. We treat the multilook case. The proposal is to estimate this parameter by minimizing the triangular distance between the G 0 density and an estimate of the underlying density function using asymmetric kernels. We assess the properties of these estimators with analytic results and simulation. We use actual images to evaluate the performance of our proposal.

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Section: Performance Analysismentioning

confidence: 73%

An Improved Minimum-Distance Texture Estimator for Speckled Data Under the $$\mathscr {G}^0$$ Model

Cassetti

Frery

2022

J Math Imaging Vis

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“…Due to the stochastic nature of speckle noise, the statistical modeling of SAR data is strategic for image interpretation (Chan et al, 2019). In (Gao, 2010), the author details different models proposed for describing these kind of data and analyzes their properties.…”

Section: Introductionmentioning

confidence: 99%

Speckle Noise Reduction in Sar Images Using Information Theory

Chan

Gambini

Frery

2020

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. In this work, a new nonlocal means filter for single-look speckled data using the Shannon and Rényi entropies is proposed. The measure of similarity between a central window and patches of the image is based on a statistical test for comparing if two samples have the same entropy and hence have the same distribution.The results are encouraging, as the filtered image has better signal-to-noise ratio, it preserves the mean, and the edges are not severely blurred.

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Parameter Estimation for Sea Clutter Pareto Distribution Model Based on Variable Interval

et al. 2022

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The generalized Pareto (GP) distribution model is often used to describe the amplitude statistical feature of sea clutter. Generally, the parameters of GP distribution are estimated by moments estimators. However, when the sea state is high, the appearance of sea spikes will increase the echo of the anomalous scattering units, which leads to a decrease in the parameter estimation accuracy and target detection performance. To improve the parameter estimation accuracy, this paper proposes a novel parameter estimation method based on variable intervals. Considering the local properties of sea clutter, we take a variable interval of the entire sea clutter series for parameter estimation, where the interval position is selected according to the sea state conditions. For contrast, the bipercentile parameter estimation and truncate moment estimation are also introduced. Finally, the experiment based on the real measured X-band sea clutter datasets indicates that the proposed method outperforms the state-of-the-art moments estimators.

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Low-Cost Robust Estimation for the Single-Look $\mathcal{G}_{I}^{0}$ Model Using the Pareto Distribution

Cited by 3 publications

References 21 publications

An Improved Minimum-Distance Texture Estimator for Speckled Data Under the $$\mathscr {G}^0$$ Model

An Improved Minimum-Distance Texture Estimator for Speckled Data Under the $$\mathscr {G}^0$$ Model

Speckle Noise Reduction in Sar Images Using Information Theory

Parameter Estimation for Sea Clutter Pareto Distribution Model Based on Variable Interval

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