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Comparing samples from the G 0 G0 distribution using a geodesic distance

  • Alejandro C. Frery [1] ; Juliana Gambini [2]
    1. [1] Universidade Federal de Alagoas

      Universidade Federal de Alagoas

      Brasil

    2. [2] Depto. de Ingeniería Informática, Instituto Tecnológico de Buenos Aires, Av. Madero 399, C1106ACD, Buenos Aires, Argentina
  • Localización: Test: An Official Journal of the Spanish Society of Statistics and Operations Research, ISSN-e 1863-8260, ISSN 1133-0686, Vol. 29, Nº. 2, 2020, págs. 359-378
  • Idioma: inglés
  • DOI: 10.1007/s11749-019-00658-2
  • Texto completo no disponible (Saber más ...)
  • Resumen
    • The G0G0 distribution is widely used for monopolarized SAR image modeling because it can characterize regions with different degrees of texture accurately. It is indexed by three parameters: the number of looks (which can be estimated for the whole image), a scale parameter and a texture parameter. This paper presents a new proposal for comparing samples from the G0G0distribution using a geodesic distance (GD) as a measure of dissimilarity between models. The objective is quantifying the difference between pairs of samples from SAR data using both local parameters (scale and texture) of the G0G0distribution. We propose three tests based on the GD which combine the tests presented in Naranjo-Torres et al. (IEEE J Sel Top Appl Earth Obs Remote Sens 10(3):987–997, 2017), and we estimate their probability distributions using permutation methods.

  • Referencias bibliográficas
    • Atkinson C, Mitchell AF (1981) Rao’s distance measure. Sankhyā: Indian J Stat Ser A (1961-2002) 43:345–365
    • Berry KJ, Johnston JE, Mielke PW (2011) Permutation methods. Wiley Interdiscip Rev Comput Stat 3(6):527–42. https://doi.org/10.1002/wics.177...
    • Berry KJ, Johnston JE, Mielke PW, Johnston LA (2018) Permutation methods. Part II. Wiley Interdiscip Rev Comput Stat 10:e1429. https://doi.org/10.1002/wics.1429...
    • Broyden CG (1965) A class of methods for solving nonlinear simultaneous equations. Math Comput 19:577–593
    • Bustos OH, Frery AC (1992) Reporting Monte Carlo results in statistics: suggestions and an example. Rev Soc Chil Estad 9(2):46–95
    • Chan D, Rey A, Gambini J, Frery AC (2018) Sampling from the GI0 distribution. Monte Carlo Methods Appl 24(4):271–287
    • Dell’Acqua F, Gamba P (2012) Remote sensing and earthquake damage assessment: experiences, limits, and perspectives. Proc IEEE 100(10):2876–2890
    • Feinstein AR (1993) Permutation tests and statistical significance. M. D. Comput Comput Med Pract 10:28–41
    • Fisher KA (1934) Statistical methods for research workers, 5th edn. Oliver & Boyd, Edinburgh
    • Frery AC, Müller H-J, Yanasse CCF, Sant’Anna SJS (1997) A model for extremely heterogeneous clutter. IEEE Trans Geosci Remote Sens 35(3):648–659
    • Frery AC, Cribari-Neto F, Souza MO (2004) Analysis of minute features in speckled imagery with maximum likelihood estimation. EURASIP J Appl...
    • Gambini J, Mejail M, Jacobo-Berlles J, Frery A (2006) Feature extraction in speckled imagery using dynamic B-spline deformable contours under...
    • Gambini J, Mejail M, Jacobo-Berlles J, Frery AC (2008) Accuracy of edge detection methods with local information in speckled imagery. Stat...
    • Gambini J, Cassetti J, Lucini M, Frery A (2015) Parameter estimation in SAR imagery using stochastic distances and asymmetric kernels. IEEE...
    • Henningsen A, Toomet O (2011) maxLik: a package for maximum likelihood estimation in R. Comput Stat 26(3):443–458
    • Hill MJ, Ticehurst CJ, Lee J-S, Grunes MR, Donald GE, Henry D (2005) Integration of optical and radar classifications for mapping pasture...
    • Ilea I, Bombrun L, Germain C, Terebes R, Borda M (2015) Statistical hypothesis test for robust classification on the space of covariance matrices....
    • Marques RCP, Medeiros FN, Santos Nobre J (2012) SAR image segmentation based on level set approach and G0AGA0 model. IEEE Trans Pattern Anal...
    • Menendez ML, Morales D, Pardo L, Salicru M (1995) Statistical test based on the geodesic distances. Appl Math Lett 8(1):65–69
    • Naranjo-Torres J, Gambini J, Frery AC (2017) The geodesic distance between G0IGI0 models and its application to region discrimination. IEEE...
    • Nascimento ADC, Cintra RJ, Frery AC (2010) Hypothesis testing in speckled data with stochastic distances. IEEE Trans Geosci Remote Sens 48(1):373–385
    • Quartulli M, Datcu M (2004) Stochastic geometrical modelling for built-up area understanding from a single SAR intensity image with meter...
    • R Core Team (2016) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
    • Rao CR (1945) Information and the accuracy attainable in the estimation of statistical parameters. Bull Calcutta Math Soc 37:81–91
    • Rao CR (1992) Information and the accuracy attainable in the estimation of statistical parameters. In: Kotz S, Johnson NL (eds) Breakthroughs...
    • Salicrú M, Morales D, Menéndez ML, Pardo L (1994) On the applications of divergence type measures in testing statistical hypotheses. J Multivar...
    • Silva WB, Freitas CC, Sant’Anna SJS, Frery AC (2013) Classification of segments in PolSAR imagery by minimum stochastic distances between...
    • Storie CD, Storie J, Salinas de Salmuni G (2012) Urban boundary extraction using 2-component polarimetric SAR decomposition. In: IEEE international...
    • Sun W, Shi L, Yang J, Li P (2016) Building collapse assessment in urban areas using texture information from postevent SAR data. IEEE J Sel...
    • Verdoolaege G, Scheunders P (2011) Geodesics on the manifold of multivariate generalized Gaussian distributions with an application to multicomponent...
    • Verdoolaege G, Scheunders P (2012) On the geometry of multivariate generalized Gaussian models. J Math Imaging Vis 43(3):180–193

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