An Adaptive General Four-Component Scattering Power Decomposition With Unitary Transformation of Coherency Matrix (AG4U)

Bhattacharya, Avik; Singh, Gulab; Manickam, Surendar; Yamaguchi, Yoshio

doi:10.1109/lgrs.2015.2451369

Cited by 56 publications

(32 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Dependence of β on the soil dielectric constant at different incidence angles. s [2,41] ε ∈ , [25,55] θ ∈ . Dependence of absolute value of α on the dielectric constant of soil and trunk when incidence angle is 25 degrees and with zero polarimetric phase difference.…”

Section: Variable Transformationmentioning

confidence: 99%

See 1 more Smart Citation

Quantitative Analysis of Polarimetric Model-Based Decomposition Methods

et al. 2016

View full text Add to dashboard Cite

Abstract:In this paper, we analyze the robustness of the parameter inversion provided by general polarimetric model-based decomposition methods from the perspective of a quantitative application. The general model and algorithm we have studied is the method proposed recently by Chen et al., which makes use of the complete polarimetric information and outperforms traditional decomposition methods in terms of feature extraction from land covers. Nevertheless, a quantitative analysis on the retrieved parameters from that approach suggests that further investigations are required in order to fully confirm the links between a physically-based model (i.e., approaches derived from the Freeman-Durden concept) and its outputs as intermediate products before any biophysical parameter retrieval is addressed. To this aim, we propose some modifications on the optimization algorithm employed for model inversion, including redefined boundary conditions, transformation of variables, and a different strategy for values initialization. A number of Monte Carlo simulation tests for typical scenarios are carried out and show that the parameter estimation accuracy of the proposed method is significantly increased with respect to the original implementation. Fully polarimetric airborne datasets at L-band acquired by German Aerospace Center's (DLR's) experimental synthetic aperture radar (E-SAR) system were also used for testing purposes. The results show different qualitative descriptions of the same cover from six different model-based methods. According to the Bragg coefficient ratio (i.e., β), they are prone to provide wrong numerical inversion results, which could prevent any subsequent quantitative characterization of specific areas in the scene. Besides the particular improvements proposed over an existing polarimetric inversion method, this paper is aimed at pointing out the necessity of checking quantitatively the accuracy of model-based PolSAR techniques for a reliable physical description of land covers beyond their proven utility for qualitative features extraction.

show abstract

Section: Variable Transformationmentioning

confidence: 99%

“…Dependence of β on the soil dielectric constant at different incidence angles. s [2,41] ε ∈ , [25,55] θ ∈ . …”

Section: Variable Transformationmentioning

confidence: 99%

Quantitative Analysis of Polarimetric Model-Based Decomposition Methods

et al. 2016

View full text Add to dashboard Cite

show abstract

“…Real rotation (T (θ)) in 2B, first complex rotation (T (ϕ1)) in 2C, and second complex rotation (T(ϕ2)) in 2D are subsequently performed on symmetrical Hermitian semi-definite matrix known as a coherency matrix (T) [8], [9]. It will help to reduce cross polarization, which is responsible for the overestimation of the volume scattering.…”

Section: Fig 1 Proposed Methodology Flowchartmentioning

confidence: 99%

Detection of Marine Vessels Based on Variation of Degree of Polarization

Dashondhi

Buddhiraju

2018

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

View full text Add to dashboard Cite

<p><strong>Abstract.</strong> For improving security of any country, satellite images are playing vital role. Vessels detection using SAR imagery is one of the primary requirements for maritime surveillance. In this paper, the algorithm used for vessels detection has four parts. The first part includes pre-processing to reduce speckle noise, second part helps in the reduction of cross polarization by real and complex rotation of the coherency matrix, third part derives a new parameter called variation of degree of polarization (VD) and fourth one is a post processing part to connect region and fill gaps using morphological operation. The proposed algorithm is tested on ALOS PALSAR1 (space borne L band) and UAVSAR (Airborne L band) datasets and yielded promising results with a relatively few false alarms.</p>

show abstract

“…Therefore, instead of the one (phase angle compensation (PAC)) applied in the G4U, another special unitary matrix is considered in the SU T (3) group, as applied in the AG4U [21], i.e., …”

Section: Helix Angle Compensationmentioning

confidence: 99%

A Hierarchical Extension of General Four-Component Scattering Power Decomposition

et al. 2017

View full text Add to dashboard Cite

Abstract:The overestimation of volume scattering (OVS) is an intrinsic drawback in model-based polarimetric synthetic aperture radar (PolSAR) target decomposition. It severely impacts the accuracy measurement of scattering power and leads to scattering mechanism ambiguity. In this paper, a hierarchical extended general four-component scattering power decomposition method (G4U) is presented. The conventional G4U is first proposed by Singh et al. and it has advantages in full use of information and volume scattering characterization. However, the OVS still exists in the G4U and it causes a scattering mechanism ambiguity in some oriented urban areas. In the proposed method, matrix rotations by the orientation angle and the helix angle are applied. Afterwards, the transformed coherency matrix is applied to the four-component decomposition scheme with two refined models. Moreover, the branch condition applied in the G4U is substituted by the ratio of correlation coefficient (RCC), which is used as a criterion for hierarchically implementing the decomposition. The performance of this approach is demonstrated and evaluated with the Airborne Synthetic Aperture Radar (AIRSAR), Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR), Radarsat-2, and the Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) fully polarimetric data over different test sites. Comparison studies are carried out and demonstrated that the proposed method exhibits promising improvements in the OVS and scattering mechanism characterization.

show abstract

An Adaptive General Four-Component Scattering Power Decomposition With Unitary Transformation of Coherency Matrix (AG4U)

Cited by 56 publications

References 16 publications

Quantitative Analysis of Polarimetric Model-Based Decomposition Methods

Quantitative Analysis of Polarimetric Model-Based Decomposition Methods

Detection of Marine Vessels Based on Variation of Degree of Polarization

A Hierarchical Extension of General Four-Component Scattering Power Decomposition

Contact Info

Product

Resources

About