Publications

@article{Yahia2022,

title = {Span Statistics and Their Impacts on PolSAR Applications},

author = {M. Yahia and T. Ali and M. M. Mortula},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85097949990\&doi=10.1109%2fLGRS.2020.3039109\&partnerID=40\&md5=96cb85394308184738f919db28132a8b},

doi = {10.1109/LGRS.2020.3039109},

issn = {1545598X},

year  = {2022},

date = {2022-01-01},

journal = {IEEE Geoscience and Remote Sensing Letters},

volume = {19},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {The span is widely employed in synthetic aperture radar (SAR) polarimetry (PolSAR) applications. The span is a summation of the three polarimetric intensity channels, its probability density function (pdf) is commonly assumed in the literature as that of the intensity polarimetric channel. In this letter, the statistics of the span are investigated. It has been demonstrated that the span is modeled by $L$ -looks intensity pdf where $L$ is the equivalent number of looks (ENLs) of the span transformation, i.e., ENLspan. To estimate ENLspan, a theoretical model has been proposed. The results showed that ENLspan ranges in [1,3] depending on the media's scattering property. Results demonstrated also that the use of the eigenvalues produced better estimation of ENLspan than the use of diagonal elements of the coherence or the covariance matrix. The proposed model produced also a more accurate estimation of ENLspan than the one obtained by the direct calculation. Finally, it has been demonstrated that the use of the introduced span statistics gave a correct estimation of the performance of the classification and the filtering PolSAR techniques whereas classical span statistics overestimated them. © 2004-2012 IEEE.},

note = {cited By 4},

keywords = {Accurate estimation; Diagonal elements; Direct calculation; Equivalent number of looks; Probability density function (pdf); Scattering property; Synthetic aperture radar polarimetries; Theoretical modeling, algorithm; detection method; satellite imagery; statistical analysis; synthetic aperture radar, Covariance matrix; Eigenvalues and eigenfunctions; Polarimeters; Synthetic aperture radar, Probability density function},

pubstate = {published},

tppubtype = {article}

}