This paper proposes a new approach in polarimetric synthetic aperture radar (SAR) speckle filtering. The new approach emphasizes preserving polarimetric properties and statistical correlation between channels, not introducing crosstalk, and not degrading the image quality. In the last decade, speckle reduction of polarimetric SAR imagery has been studied using several different approaches. All of these approaches exploited the degree of statistical independence between linear polarization channels. The preservation of polarimetric properties and statistical characteristics such as correlation between channels were not carefully addressed. To avoid crosstalk, each element of the covariance matrix must be filtered independently. This rules out current methods of polarimetric SAR filtering. To preserve the polarimetric signature, each element of the covariance matrix should be filtered in a way similar to multilook processing by averaging the covariance matrix of neighboring pixels. However, this must be done without the deficiency of smearing the edges, which degrades image quality and corrupts polarimetric properties. The proposed polarimetric SAR filter uses edge-aligned nonsquare windows and applies the local statistics filter. The impact of using this polarimetric speckle filtering on terrain classification is quite dramatic in boosting classification performance. Airborne polarimetric radar images are used for illustration.

Polarimetric SAR speckle filtering and its implication for classification

Polarimetric and interferometric SAR data are frequently multilook processed for speckle reduction and data compression. The statistical characteristics of multilook data are quite different from those of single-look data. The authors investigate the statistics of their intensity and phase. Probability density function (PDF's) of the multilook phase difference, magnitude of complex product, and intensity and amplitude ratios between two components of the scattering matrix are derived, and expressed in closed forms. The PDF's depend on the complex correlation coefficient and the number of looks. Comparisons of these theoretically derived PDF's are made to measurements from NASA/JPL AIRSAR data. The results of this paper can be applied to feature classification using polarimetric SAR and to the estimation of decorrelation effects of the interferometric SAR. >

Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery

Current speckle filters attempt to restore the radar reflectivity using only the multiplicative speckle noise assumption. The best known filters, namely the Frost, Lee or Kuan niters are adaptive filters based on the local statistics, computed in a fixed square window. In this way, the speckle is reduced as a function of the heterogeneity measured by the local coefficient of variation. When the radar reflectivity undergoes significant variations due to the presence of strong scatterers or structural features (edges or lines) in the processing window, such speckle filtering is less effective. In this paper it is shown that the filtering process can be controlled both by the coefficient of variation and by various geometrical ratio detectors. Through shape adaptive windowing, these detectors allow the use of large window sizes for better speckle reduction while preserving spatial resolution and structural features. The backscattered intensity is modelled as K-distributed within speckled targets and...

Structure detection and statistical adaptive speckle filtering in SAR images

In this work, spectral estimation techniques are used to exploit baseline diversity of a multichannel interferometric synthetic aperture radar (SAR) system and overcome the layover problem. This problem arises when different height contributions collapse in the same range-azimuth resolution cell, due to the presence of strong terrain slopes or discontinuities in the sensed scene. We propose a multilook approach to counteract the presence of multiplicative noise, which is due to the extended nature of natural targets; to this purpose we extend the RELAX algorithm to the multilook data scenario (M-RELAX). A thorough performance analysis of nonparametric (beamforming and Capon) and parametric (root MUSIC and M-RELAX) techniques is carried out based on Monte Carlo simulations and Cramer-Rao lower bounds (CRLB) calculation. The results suggest the superiority of parametric methods over nonparametric ones.

Layover solution in multibaseline SAR interferometry

This study provides an update of the polarimetric tools currently being used for optimum information extraction from polarimetric synthetic aperture radar (SAR) images. The basics of polarimetric theory are summarized and discussed in the context of SAR. Calibration of polarimetric SAR, which is an important issue for the extraction of meaningful polarization information, is reviewed. Information extraction using the scattered and received wave parameters and target decomposition theory is considered. In particular, the use of coherent versus incoherent target decomposition is discussed and the practical limitations of these target decompositions are outlined. Speckle filtering and classification of polarimetric SAR images are also thoroughly analyzed, and the important directions for future research are outlined.

A review of polarimetry in the context of synthetic aperture radar: concepts and information extraction

The information content of ordinary synthetic aperture radar (SAR) data is principally contained in the radiometric polarization channels, i.e., the four Ihh, Ivv, Ihv and Ivh backscattered intensities. In the case of clutter, polarimetric information is given by the four complex degrees of coherence, from which the mean polarization phase differences (PPD), correlation coefficients or degrees of polarization can be deduced. For radiometric features, the polarimetric parameters are corrupted by multiplicative speckle noise and by some sensor effects. The PPD distribution is related to the sensor, speckle and terrain properties. Experimental results are given for the variation of the terrain hh/vv mean phase difference and magnitude of the degree of coherence observed on bare soil and on different pine forest stands.

Phase Difference Statistics Related To Sensor And Forest Parameters

The usual polarimetric speckle filters ophally combine the polarization channels into a single image (Novak and Burl) or only restore the radiometric information (Lee et al.), i.e. the 3 Ihh, I, Ihv intensities in the r e c i p r d case. So the phase differences and the polarization channel correlation coefficients are not restored in the fdtered data. This implies a loss of information compared to the initial data, which contain in the reciprocal case 5 independent real parameters plus 1 absolute phase for 1 look scattering matrix format and 9 independent parameters for multi-look data. In this paper we develop a polarimetric minimum mean square error (MMSE) filter and a polarimetric maximum a posteriori (MAP) filter. For each pixel, one obtains on output of the filtering process either a complex "unspeckled" scattering matrix and 3 local correlation coefficients between the polarization channels for 1 look, or the 9 real parameters of the covariance matrix for multi-look images.

Polarimetric Speckle Filters For SAR Data

As the output of the SAR data processor is a complex number, speckle reduction should take profit of the additional information contained in the phase and in the complex correlation between the different images. In order to obtain high equivalent number of looks, we develop the Complex Gaussian-Gamma MAP (Maximum A Posteriori) fdter for complex multiplicative speckle noise and for K-distributed data in the case of L separate correlated complex looks data. This filter is a combination of the usual incoherent multilook processing (Doppler spectral domain) and of an adaptive spatial averaging (image spatial domain). The solution of the filter equation is very easy to handle and is the rigorous solution of the correlated looks MAP fdter.

https://ieeexplore.ieee.org/iel2/1014/12511/00578288.pdf

S. Goze

Papers

Phase Difference Statistics Related To Sensor And Forest Parameters

Polarimetric Speckle Filters For SAR Data

Adaptive Processing of Multilook Complex Sar Images