Orientation Angle Compensation Research Articles

Fundamental Study on Grasping Growth State of Paddy Rice Using Quad-Polarimetric SAR Data

In this brief paper, we examine polarimetric scattering characteristics for understanding seasonal change of paddy rice growth by using quad-polarimetric synthetic aperture radar (SAR) data in the X-band. Here we carry out polarimetric scattering measurement for a simplified paddy rice model in an anechoic chamber at X-band frequency to acquire the the quad polarimetric SAR data from the model. The measurements are performed several times for each growth stage of the paddy rice corresponding to seasonal change. The model-based scattering power decomposition is used for the examination of polarimetric features of the paddy rice model. It is found from the result of the polarimetric SAR image analysis for the measurement data that the growth state of the paddy rice in each stage can be understood by considering the ratio of the decomposition powers, when the planting direction of the paddy rice is not only normal but also oblique to radar direction. We can also see that orientation angle compensation (OAC) is useful for improving the accuracy of the growth stage observation in late vegetative stage for oblique planting case.

A Two-Stage Method for Ship Detection Using PolSAR Image

Ship detection using polarimetric SAR (PolSAR) images has recently been an active topic in the Earth observation field. There, how to detect small ships is an open and challenging issue. Within this context, we put forward a two-stage ship detection model, by which a novel ship detection method is proposed as well. Briefly, in the first stage, a suppression manipulation is adopted to suppress sea clutter, where the feature SVVS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>O</i></sub> is built on the intensity information with the orientation angle compensation (OAC). In the second stage, an enhancement manipulation is further executed to highlight ships from the suppressed sea clutter, where the features PID (polarimetric intensity difference) and NsD (nonsurface degree) are first constructed with SVVS <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>O</i></sub> and a series of theoretical derivations. Then, via fusing PID and NsD together, the two-stage-based method FPAN is proposed to detect ships. To demonstrate its performance, we apply FPAN to four different L-Band PolSAR datasets. Experimental results reveal that, compared to other state-of-the-art methods, especially the DBSP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>CP</i></sub> method, FPAN is more effective in detecting small ships. On average, its figure-of-merit (FoM) and target-to-clutter ratio (TCR) values are, respectively 9.40% and 25.18% greater than those of DBSP <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><i>CP</i></sub> , while the time consumption is just 58.67% of the latter.

Polarimetric Model-Based Decomposition with Refined Double-Bounce Orientation Angle and Scattering Model

Oriented manmade targets can produce significant cross-polarization power. The scattering mechanism interpretation of them is still challenging. Within the framework of traditional scattering models, the scattering mechanism of oriented manmade targets will be interpreted as volume scattering. Recently, many advanced approaches have been proposed to mitigate the cross-polarization terms of the coherency matrix or distribute the power of cross-polarization to new scattering models, such as orientation angle compensation and multiple scattering components decomposition. Among these methods, the general model-based decomposition with physically meaningful double-bounce and odd-bounce scattering models has been proposed by modeling their independent orientation angles and becomes a widely accepted method. However, the two vital parameters of generalized scattering models: double- and odd-bounce orientation angles are derived through nonlinear optimization procedure. These generalized models lead to a heavy computation burden for parameters inversion. In this paper, we disclose the latent relationship between the double-bounce orientation angle and polarization orientation angle by data fitting experiments. With this simplified relationship, a refined double-bounce scattering model is established. Then, the odd-bounce orientation angle can be derived through equations. In this way, the nonlinear optimization procedure can be converted to a linear solution. A fast generalized model-based decomposition is developed thereafter. The main contribution of this work is to inherit the generalized models while speeding up the parameter calculation procedure. The comparison studies are carried out with X-band airborne PiSAR, L-band spaceborne ALOS-2, and C-band spaceborne Radarsat-2 PolSAR datasets. Compared with the state-of-the-art approaches, the proposed decomposition achieves improved interpretation performance from both visual and quantitative investigations especially for oriented built-up areas.

Demonstration and Analysis of an Extended Adaptive General Four-Component Decomposition

The overestimation of volume scattering is an essential shortcoming of the model-based polarimetric synthetic aperture radar (PolSAR) target decomposition method. It is likely to affect the measurement accuracy and result in mixed ambiguity of the scattering mechanism. In this article, an extended adaptive four-component decomposition method with multiple thresholds is proposed. First, the orientation angle compensation is applied to the coherency matrix, and artificial areas are extracted as the basis for selecting the decomposition method. Second, for the decomposition of artificial areas, one of the two complex unitary transformation matrices of the coherency matrix is selected according to the wave anisotropy (A <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">w</sub> ). In addition, the branch condition that is used as a criterion for the hierarchical implementation decomposition is the ratio of the correlation coefficient (R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">cc</sub> ). Finally, the selected unitary transformation matrix and the discriminative threshold are used to determine the structure of the selected volume scattering models, which are more effective to adapt to various scattering mechanisms. In this article, the performance of the proposed method is evaluated on GaoFen-3 full PolSAR datasets for various time periods and regions. The experimental results demonstrate that the proposed method can effectively represent the scattering characteristics of the ambiguous regions, and the oriented building areas can be well discriminated as dihedral or odd-bounce structures.

A Modified Four-Component Decomposition Method With Refined Volume Scattering Models

In this article, a modified four-component decomposition method with refined volume scattering models is proposed for polarimetric synthetic aperture radar (SAR) image processing. In the new decomposition method, after the orientation angle compensation, the orientation angle is placed in the probability density functions. General forms of the volume scattering models and branch conditions can be obtained. Similar to the four-component scattering power decomposition with extended volume scattering model (S4R) proposed by Sato et al. , refined volume scattering models can be used for various land covers based on the criteria. Since the orientation angles are contained in the refined volume scattering models, the oriented buildings can be discriminated from the vegetation areas and the overestimation problem of volume scattering is substantially overcome. In this article, the performance of the proposed method is evaluated by the spaceborne C-band Gaofen-3 data and airborne L-band E-SAR data. Several approaches are employed as a comparison of the proposed methods. Experimental results show that, compared with the existing decomposition methods, the proposed method can effectively represent the scattering characteristics of the ambiguous regions, and the double-bounce scattering contributions over the urban areas can be substantially enhanced.

Seven-Component Scattering Power Decomposition of POLSAR Coherency Matrix

Applications of fully polarimetric synthetic aperture radar (POLSAR) have increased in the past few decades. The potential of model-based decompositions is coupled with polarimetric information extraction from the POLSAR data for target identification and classification. The coherency matrix $[T]$ with nine independent parameters, and associated with some physical scattering models, serves as input to these decompositions. This paper attempts to assign one such physical scattering model to the real part of $T_{23}$ ( $\text {Re}\{{T}_{23}\}$ ) and develop a new scattering power decomposition model, called as the seven-component scattering decomposition (7SD). Previously developed scattering power models have eliminated $\text {Re}\{T_{23}\}$ , assuming the orientation angle compensation condition, to reduce the number of independent $[T]$ parameters. The proposed 7SD model has been tested on fully polarimetric SAR data sets acquired by the spaceborne Advanced Land Observing Satellite-2/Phased Array type L-band Synthetic Aperture Radar-2 (ALOS-2/PALSAR-2) and airborne F-SAR, and the results are compared with the existing scattering power decompositions. The physical scattering model for $\text {Re}\{T_{23}\}$ is derived from a particular configuration of dipoles (referred to as “mixed dipole” configuration), which gives rise to compound scattering. The mixed-dipole scattering occurs in urban areas that are highly oriented to the radar illumination direction as well as in vegetation areas. 7SD also delivers an additional mixed dipole scattering power compared to the previous six-component scattering model. The mixed-dipole scattering model reduces the contribution of volume scattering power in double-bounce predominant areas (such as oriented urban blocks), thereby imparting improved understanding of the polarimetric information contained in the coherency matrix.

A Hierarchical Extended Multiple-Component Scattering Decomposition of Polarimetric SAR Interferometry

In this letter, a hierarchical extended multicomponent decomposition method (ExMCSM) of polarimetric synthetic aperture radar interferometry (PolInSAR) is proposed. The target of this method is to overcome the overestimation of volume scattering (OVS) and to mitigate the mixed ambiguity of the scattering mechanism. In the proposed method, prior to the decomposition, orientation angle compensation (OAC), and helix angle compensation (HAC) are applied to the coherency matrix to reduce the complexity of the operation. The polarimetric interferometric similarity parameter (PISP) is used to refine the volume scattering models, and the optimal coherence magnitude (γ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">opt3</sub> ) is used as a criterion for the adaptive selection of these volume scattering models. The efficiency of the proposed method is demonstrated using two different test sites. Experimental results demonstrate that the proposed method can effectively represent the scattering characteristics of the ambiguous regions.

A hierarchical extension of a multiple-component scattering model with unitary transformation of the coherency matrix

ABSTRACTThe overestimation of volume scattering (OVS) is an essential shortcoming of the model-based polarimetric synthetic aperture radar (PolSAR) target decomposition method. It is likely to affect the measurement accuracy and result in mixed ambiguity of the scattering mechanism. In this paper, a hierarchical extended multi-component decomposition method (ExMCSM) that can adaptively select the refined volume scattering models based on the artificial area extraction result is proposed for overcoming the OVS. First, artificial areas are extracted from the image to distinguish between artificial areas and non-artificial areas. Then, orientation angle compensation (OAC) and helix angle compensation (HAC) are applied to the coherency matrix to reduce the complexity of the operation. Finally, the volume scattering model of each pixel is refined to more effectively adapt to various scattering mechanisms. Spaceborne Gaofen-3 full PolSAR data are used to evaluate the performance of the proposed decomposition method. The experimental results demonstrate that the proposed decomposition method can accurately represent the scattering characteristics of the ambiguous regions and the oriented building areas can be well discriminated as dihedral or odd-bounce structures.

Building damage assessment using a single post-earthquake PolSAR image: a case of the 2010 Yushu earthquake

Earthquakes are one of the most destructive natural disasters. Efficiently and quickly acquiring building earthquake damage information can help to reduce the casualties after an earthquake. In this paper, building damage information is extracted using a single post-earthquake PolSAR image. In PolSAR images, since the undamaged oriented buildings characterized by volume scattering with weaker scattering power are very similar to collapsed buildings, the collapsed buildings are difficult to extract accurately. In this paper, the difference in the relative contribution change rate of scattering components before and after polarization orientation angle (POA) compensation is proposed to enhance the difference between collapsed buildings and oriented buildings, in order that the collapsed buildings can be extracted more accurately. The “4.14” Yushu earthquake, which occurred in Yushu County, Qinghai province of China, is used as the case study to test the proposed method, and an airborne high-resolution PolSAR image of the urban region of Yushu County is used in the experiment. The experimental results show that the accuracy of building damage information extraction can be improved by the use of the proposed method, compared with the traditional polarimetric classification.

ALTERNATIVE TO FOUR-COMPONENT DECOMPOSITION FOR POLARIMETRIC SAR

There are more unknowns than equations to solve for previous four-component decomposition methods. In this case, the nonnegative power of each scattering mechanism has to be determined with some assumptions and physical power constraints. This paper presents a new decomposition scheme, which models the measured matrix after polarimetric orientation angle (POA) compensation as a linear sum of five scattering mechanisms (i.e., odd-bounce scattering, double-bounce scattering, diffuse scattering, volume scattering, and helix scattering). And the volume scattering power is calculated by a slight modified NNED method, owing to this method considering the external volume scattering model from oblique dihedral structure. After the helix and volume scattering powers have been determined sequentially, the other three scattering powers are estimated by combining the generalized similarity parameter (GSP) and the eigenvalue decomposition. Among them, due to POA compensation, the diffuse scattering induced from a dihedral with a relative orientation of 45º has negligible scattering power. Thus, the new method can be reduced as four-component decomposition automatically. And then the ALOS-2 PolSAR data covering Guiyang City, Guizhou Province, China were used to evaluate the performance of the new method in comparison with some classical decomposition methods (i.e. Y4R, S4R and G4U).

ALTERNATIVE TO FOUR-COMPONENT DECOMPOSITION FOR POLARIMETRIC SAR

Abstract. There are more unknowns than equations to solve for previous four-component decomposition methods. In this case, the nonnegative power of each scattering mechanism has to be determined with some assumptions and physical power constraints. This paper presents a new decomposition scheme, which models the measured matrix after polarimetric orientation angle (POA) compensation as a linear sum of five scattering mechanisms (i.e., odd-bounce scattering, double-bounce scattering, diffuse scattering, volume scattering, and helix scattering). And the volume scattering power is calculated by a slight modified NNED method, owing to this method considering the external volume scattering model from oblique dihedral structure. After the helix and volume scattering powers have been determined sequentially, the other three scattering powers are estimated by combining the generalized similarity parameter (GSP) and the eigenvalue decomposition. Among them, due to POA compensation, the diffuse scattering induced from a dihedral with a relative orientation of 45º has negligible scattering power. Thus, the new method can be reduced as four-component decomposition automatically. And then the ALOS-2 PolSAR data covering Guiyang City, Guizhou Province, China were used to evaluate the performance of the new method in comparison with some classical decomposition methods (i.e. Y4R, S4R and G4U).

Improved SMB speckle filtering of polarimetric SAR data with synergistic use of orientation angle compensation and spatial majority rule

The scattering-model-based (SMB) speckle filtering for polarimetric SAR (PolSAR) data is reasonably effective in preserving dominant scattering mechanisms. However, the efficiency strongly depends on the accuracies of both the decomposition and classification of the scattering properties. In addition, a relatively weak speckle reduction particularly in distributed media was reported in the related literatures. In this work, an improved SMB filtering strategy is proposed considering the aforementioned deficiencies. First, the orientation angle compensation is incorporated into the SMB filtering process to remedy the overestimation of the volume scattering contribution in the Freeman-Durden decomposition. In addition, an algorithm to select the homogenous pixels is developed based on the spatial majority rule for adaptive speckle reduction. We demonstrate the superiority of the proposed methods in terms of scattering property preservation and speckle noise reduction using L-band PolSAR data sets of San Francisco that were acquired by the NASA/JPL airborne SAR (AIRSAR) system.

Fast building damage mapping using a single post-earthquake PolSAR image: a case study of the 2010 Yushu earthquake

Earthquakes are one of the most destructive natural disasters. Efficiently and quickly acquiring building earthquake damage information can help to reduce the casualties after an earthquake. In this paper, for convenience, speed, and precision, building damage information is extracted using a single post-earthquake PolSAR image. In PolSAR images, the undamaged parallel buildings characterized by double-bounce scattering are different from the collapsed buildings characterized by volume scattering, but the undamaged oriented buildings are very similar to collapsed buildings because of their scattering mechanism ambiguity in the early traditional model-based decomposition. Therefore, the collapsed buildings are difficult to extract accurately. In this paper, the scheme of polarization orientation angle (POA) compensation is employed to enhance the double-bounce scattering power of the oriented buildings, and the difference in the relative contribution change rate of scattering components before and after POA compensation is proposed to further enhance the difference between collapsed buildings and oriented buildings, in order that the collapsed buildings can be extracted more accurately. The “4.14” Yushu earthquake, which occurred in Yushu County, Qinghai province of China, is used as the case study to test the proposed method, and an airborne high-resolution PolSAR image of the urban region of Yushu County is used in the experiment. The experimental results show that the accuracy of building damage information extraction can be improved by the use of the proposed method, compared with the traditional polarimetric classification.

Building Earthquake Damage Information Extraction from a Single Post-Earthquake PolSAR Image

After an earthquake, rapidly and accurately obtaining building damage information can help to effectively guide the implementation of the emergency rescue and can reduce disaster losses and casualties. Using a single post-earthquake fully-polarimetric synthetic aperture radar (PolSAR) image to interpret building damage information not only involves a guaranteed data source but is also easy and can be rapidly implemented. This paper is focused on rapid building earthquake damage detection in urban areas using post-earthquake PolSAR data. In PolSAR images, the undamaged buildings parallel to satellite flight pass are different from the collapsed buildings, but the undamaged buildings divergent to satellite flight pass are very similar to collapsed buildings because of their volume scattering characteristics. In this paper, the method of polarization orientation angle (POA) compensation is employed to increase the scattering power of buildings divergent to satellite flight pass, and then Wishart supervised classification is implemented on the PolSAR data after POA compensation. In addition, the two parameters of normalized difference of the dihedral component (NDDC) and ρHHHV are proposed to improve the classification accuracy of the Wishart supervised classification, and both the undamaged buildings and collapsed buildings are determined. The study was carried out after the “4.14” Yushu earthquake in Yushu County, Qinghai province, China. The three damage levels are set for the urban area at the city block scale according to the values of the BBCR building damage index. The experimental results confirm that the scheme proposed in this paper can greatly improve the accuracy of the extraction of building damage information.

Dynamic Arc Fitting Path Follower for Skid-Steered Mobile Robots

Many applications, such as surveillance, inspection or search and rescue operations, can be performed with autonomous robots. Our aim is a control of modular autonomous systems in rescue robotics. One of the basic problems with autonomous robotics is the execution part where the control commands (translation and rotational velocities) are produced for mobile bases. Therefore we have focused on this area because there is only a small amount of available path following software for skid-steered mobile robots. Our goal was to develop a velocity controller that could be used for multiple skid-steered mobile bases. We considered differential drive mobile bases such as tracked skid-steering mobile bases. Our approach is based on an arc fitting algorithm, which takes into account the robot constraints and kinematical model. It produces a continuous trajectory where fitting to the given path is adapted based on given parameters. Moreover, we have included orientation angle compensation while the mobile robot is moving and ground inclination compensation. Our rescue robot is described, together with the simulation setup and algorithm implementation. We compared our algorithm to the Hector-based software and curvature velocity approach. The results for the proposed algorithm are shown for the simulation results and the experiment.

Improved van Zyl Polarimetric Decomposition Lessening the Overestimation of Volume Scattering Power

This paper improves van Zyl’s Nonnegative Eigenvalue Decomposition (NNED). Orientation angle compensation and helix scattering are introduced to the decomposition. The volume scattering parameters that explain the most cross-polarized power are selected. If volume scattering and helix scattering explain all cross-polarized power in the measured coherency matrix, then simply perform van Zyl decomposition to the remainder matrix; otherwise, the measured coherency matrix is decomposed into three components, i.e., helix scattering, volume scattering, and one ground scattering. The latter two scattering are all modeled by Neumann’s adaptive depolarizing model, according to which some cross-polarized power is attributed to ground scattering hence the orientation angle randomness of volume scattering and the dominant ground scattering are obtained. In this way, all cross-polarized power could be well explained. Experiments using UAVSAR data showed that more than 99.8% of total pixels are well fitted. Negative power is avoided. Compared with van Zyl decomposition, volume scattering power is reduced by up to 8.73% on average. The given volume scattering power is often lower than that by three latest NNED.

General Polarimetric Model-Based Decomposition for Coherency Matrix

Orientation angle compensation was incorporated into model-based decomposition to cure overestimation of the volume scattering contribution for interpretation of polarimetric synthetic aperture radar (PolSAR) data. The compensation is based on rotating the coherency matrix to minimize the cross-polarization term. However, this processing cannot always guarantee that the double- and odd-bounce scattering components will be rotated back to zero orientation angle and left with zero cross-polarization power. As a result, built-up patches with large orientation angles may still suffer from the scattering mechanism ambiguity. In this paper, double- and odd-bounce scattering models were generalized to fit the cross-polarization and off-diagonal terms, by separating their independent orientation angles. A general decomposition framework is proposed that utilizes all elements of a coherency matrix. The residual minimization criterion is used for model inversion. All the model parameters are simultaneously obtained using a nonlinear least squares optimization technique. The manual intervention, branch conditions, and negative power issues are avoided. The performance and advantages of this approach are demonstrated and evaluated with spaceborne L-band ALOS/PALSAR and airborne X-band Pi-SAR PolSAR data sets. Comparison studies are also carried out and demonstrate that further improved decomposition performance is achieved by the proposed method, especially in oriented built-up areas.

Improved Four-Component Model-Based Target Decomposition for Polarimetric SAR Data

An improved four-component model-based target decomposition scheme for polarimetric synthetic aperture radar data is proposed in this letter. The reason for the emergence of the negative powers in the Yamaguchi decomposition has been analyzed, and three corresponding additional steps are added in the proposed scheme. First, the orientation angle compensation is applied to the coherency matrix. Second, the coherency matrix with the maximum entropy, i.e., the identity matrix is used as the volume scattering model instead of the traditional ones. Third, corresponding power constraints are appended to the scheme. Moreover, the densely vegetated areas and the residual areas are processed separately via the H/α/A classification in the proposed scheme. Finally, the polarimetric-scattering-characteristic-preserving classification is utilized to verify the improvements of the proposed scheme. To demonstrate the effectiveness of the decomposition, an Advanced Land Observing Satellite Phased-Array-type L-band Synthetic Aperture Radar polarimetric image acquired over Beijing, China, is analyzed, and the results are presented in this letter. With negative powers eliminated by the proposed scheme, improvements can be observed in the experimental results, particularly for the urban areas.

Orientation Angle Calibration for Bare Soil Moisture Estimation Using Fully Polarimetric SAR Data

This paper focuses on assessing the effectiveness of applying orientation angle calibration to polarimetric synthetic aperture radar (PolSAR) data for soil moisture estimation. We employ Cloude-decomposition-based method to estimate the orientation angle because it can relate a scatter-distributed pixel to its major component of an equivalent "pure target," use the Jet Propulsion Laboratory/Airborne Synthetic Aperture Radar L-band fully polarimetric data to validate the proposed method, and observe results in good agreement after orientation angle compensation is employed. Specifically, root mean square errors of measured radar backscattering coefficients σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hh</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> and σ <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">vv</sub> <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">0</sup> and copolarization ratio versus advanced integral equation model predictions are reduced significantly from 1.95, 1.33, and 2.03 dB to 1.30, 1.15, and 1.43 dB, respectively. The compensated copolarized backscattering coefficients are also used as inputs to a novel inversion model to estimate the dielectric factor R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hh</sub> and volumetric soil moisture m <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</sub> . The results show that the estimation errors are reduced significantly from 0.075 to 0.054 and 0.056 to 0.041 for R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">hh</sub> and m <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">v</sub> , respectively. This paper demonstrates the advantage of orientation angle calibration as a preprocessing for estimating bare soil moisture, particularly in agricultural areas, and the preponderance of fully PolSAR data on soil moisture estimation over dual and single polarizations.

The Effect of Orientation Angle Compensation on Coherency Matrix and Polarimetric Target Decompositions

The polarization orientation angle (OA) of the scattering media affects the polarimetric radar signatures. This paper investigates the effects of orientation compensation on the coherency matrix and the scattering-model-based decompositions by Freeman-Durden and Yamaguchi et al. The Cloude and Pottier decomposition is excluded, because entropy, anisotropy, and alpha angle are roll invariant. We will show that, after orientation compensation, the volume scattering power is consistently decreased, while the double-bounce power has increased. The surface scattering power is relatively unchanged, and the helicity power is roll invariant. All of these characteristics can be explained by the compensation effect on the nine elements of the coherency matrix. In particular, after compensation, the real part of the (HH - VV) · HV* correlation reduces to zero, the intensity of cross-pol |HV| always reduces, and |HH - VV| always increases. This analysis also reveals that the common perception that OA compensation would make a reflection asymmetrical medium completely reflection symmetric is incorrect and that, contrary to the general perception, the four-component decomposition does not use the complete information of the coherency matrix. Only six quantities are included - one more than the Freeman-Durden decomposition, which explicitly assumes reflection symmetry.