We propose an original concept of compressive sensing (CS) polarimetric imaging based on a digital micro-mirror (DMD) array and two single-pixel detectors. The polarimetric sensitivity of the proposed setup is due to an experimental imperfection of reflecting mirrors which is exploited here to form an original reconstruction problem, including a CS problem and a source separation task. We show ...

Abstract. This study presents the first-ever complete characterization of random errors in dual-polarimetric spectral observations meteorological targets by cloud radars. The is given means mathematical equations for joint probability density functions (PDFs) and error covariance matrices. derived are checked consistency using real radar measurements. One main conclusions that convenient repres...

in this paper, the potential of polarimetric sar data using target decomposition features to detect oil pollutions are evaluated. for this purpose, the values of power, phase and magnitude of all of the polarization channels (hh, vv, hv and vh) and decomposition features i.e. freeman, yamaguchi, vanzyl and krogager are computed. then, to detect oil pollutions, different combinations of these fe...

Polarimetric calibration accuracy is a key factor in the quantitative use of polarimetric SAR data as well as the design of future SAR system. This paper presents an approach to determine the maximum acceptable distortion level remaining after polarimetric calibration in Polarimetric SAR Interferometry (Pol-InSAR). PolInSAR distortion model of calibration is reviewed and discussed firstly. Then...

Electromagnetic scattering is fundamentally a vector process. Therefore, to capture all the information from the scattered waves, the full polarization vector of the waves received by the radar should be measured. Polarimetric SARs were first demonstrated in the early 1980s, and made their debut in space with the SIR-C/X-SAR mission in 1994. By the end of the 1990’s several polarimetric airborn...

The visualization of fully polarimetric radar data is hindered by traditional remote sensing methodologies for displaying data due to the large number of parameters per pixel in such data, and the non-scalar nature of variables such as phase difference. In this paper, a new method is described that uses icons instead of image pixels to represent the image data so that polarimetric properties an...

Polarimetric decomposition and classification are important applications for polarimetric synthetic aperture radar (POLSAR) images. Among many methods developed so far, entropy-anisotropy-alpha classification [1] and three component decomposition [2] are most popular. In an urban area analysis, it is found that the polarimetric analysis has a problem to identify built-up areas. With the three c...

Radar based surface soil moisture retrieval has been subject of intense research during the last decades. However, the space-borne radar sensors available so far provided single configuration observations where the influence of surface roughness generally caused the solution of the backscattering process to be ill posed. The availability of SAR sensors with polarimetric capabilities, such as RA...

The classification of polarimetric SAR image based on Multiple-Component Scattering Model (MCSM) and Support Vector Machine (SVM) is presented in this paper. MCSM is a potential decomposition method for a general condition. SVM is a popular tool for machine learning tasks involving classification, recognition, or detection. The scattering powers of single-bounce, doublebounce, volume, helix, an...

We explore the prospects for simultaneous, broad-band, multiwavelength polarimetric observations of GRB afterglows. We focus on the role of cosmic dust in GRB host galaxies on the observed percentage polarization of afterglows in the optical/near-infrared bands as a function of redshift. Our driving point is the afterglow of GRB 030329, for which we obtained polarimetric data in the R band and ...