• Non ci sono risultati.

e SHEMDIN O.H., Models for Synthetic Aperture Radar Imaging of the Ocean: A Comparison, Journal of Geophysical Research, Vol

N/A
N/A
Protected

Academic year: 2021

Condividi "e SHEMDIN O.H., Models for Synthetic Aperture Radar Imaging of the Ocean: A Comparison, Journal of Geophysical Research, Vol"

Copied!
3
0
0

Testo completo

(1)

142

BIBLIOGRAFIA

[1] CURLANDER J.C. e MCDONOUGH R.N., Synthetic Aperture Radar, System and Signal Processing, Wiley Interscience, 1991.

[2] APEL J. R., Principles of Ocean Physic, International Geophysics Series, Vol. 38, 1998.

[3] KASILINGAM D.P. e SHEMDIN O.H., Models for Synthetic Aperture Radar Imaging of the Ocean: A Comparison, Journal of Geophysical Research, Vol. 95, pp.

16263-16276, 1990.

[4] ULABY F.T., MORE R.K. e FUNG A.K., Microwave Remote Sensing, Artech House Inc., Norwood, 1996.

[5] BERIZZI F., e DALLE MESE E., I Sistemi Attivi di Telerilevamento a Microonde, Libro Multimediale in fase di stesura, Cap. 8.

[6] HASSELMANN K. e HASSELMANN S., On the Nonlinear Mapping of an Ocean Wave Spectrum into a Synthetic Aperture Radar Image Spectrum and its Inversion, Journal of Geophysical Research, Vol. 96, 1991.

[7] KROGSTAD H.E., A Simple Derivation of Hasselmann’s Nonlinear Ocean- Synthetic Aperture Radar Transform, Journal of Geophysical Research, Vol. 97, 1992.

[8] MONALDO F.M. e LYZENGA D.R., On the Estimation of Wave Slope and Height Variance Spectra from SAR Imagery, IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-24, pp. 543-551, 1986.

[9] MONALDO F.M., GERLING T.G. e TILLEY D.G., Comparison of SIR-B SAR Image Spectra with Wave Model Prediction: Implications on the SAR Modulation Transfer Function, IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-31, 1993.

[10] ALPERS W.R., RUFENACH C.L. e ROSS D.B., On the Detectability of Ocean Surface Waves by Real and Synthetic Aperture Radar, Journal of Geophysical Research, Vol. 86, pp. 6481-6498, 1981.

[11] TUCKER M.J., The Imaging of Waves by Satelliteborne Synthetic Aperture Radar: the Effects of Sea-Surface Motion, International Journal on Remote Sensing, Vol. 6, pp. 1059-1074, 1985.

[12] ALPERS W.R. e RUFENACH C.L., The Effect of Orbital Motions on Synthetic Aperture Radar Imagery of Ocean Waves, IEEE Trans. on Antennas and Propagation, Vol. AP-27, 1979.

[13] VACHON P.W. e RANEY R.K., Resolution of the Ocean Wave Propagation Direction in SAR Imagery, IEEE Trans. on Antennas and Propagation, Vol. AP-29, 1991.

[14] MONORCHIO A., SAR Imaging di Superfici Marine: Simulazione ed Estrazione di Parametri Fisici, Dottorato di Ricerca in “Metodi e Tecnologie per il Monitoraggio Ambientale”.

[15] VERRAZZANI L., La Teoria della Decisione e della Stima nelle Applicazioni di Telecomunicazione, Edizioni ETS, 1996.

[16] THERRIENC. W., Discrete Random Signals and Statistical Signal Processing, Prentice Hall, Englewood Cliffs, 1992.

(2)

Bibliografia

143

[17] KAY S.M., Modern Spectral Estimation, Theory and Application, Prentice Hall, Englewood Cliffs, 1988.

[18] OPPENHEIM A.V. e SCHAFER R.W., Digital Signal Processing, Prentice- Hall, Englewood Cliffs, New Jersey, 1975.

[19] KOLMOGOROV A.N., Local Structure of Turbulence in Fluid for Very Large Reynolds Numbers, Transl. in Turbulence, S. K. Friedlander and L. Topper (eds.), 1961, Interscience Publishers, New York, pp. 151-155.

[20] MANDELBROT B.B. e VAN NESS J.W., Fractional Brownian motions, fractional noises and Applications, SIAM Rev. 10, pp. 422-437, 1968.

[21] MANDELBROT B.B. e WALLIS J.R., Noah, Joseph and Operational Hydrology, Water Resources Res., 4, pp. 909-918, 1968.

[22] MANDELBROT B.B. e WALLIS J.R., Robustness of the Rescaled Range R/S and the Measurement of Non-Cyclic Long-Run Statistical Dependence, Water Resources Res., 5, pp. 967-988, 1968.

[23] MANDELBROT B.B. e WALLIS J.R., Computer Experiments with fractional Gaussian noises, Water Resources Res., 5, pp. 228-267, 1969.

[24] WILLINGER W., et al., Self-Similarity in High-Speed Packet Traffic: Analysis and Modeling of Ethernet Traffic Measurements, Stat. Sci., pp. 67-85, 1995.

[25] ROSE O., Estimation of the Hurst Parameter of Long-Range Dependent Time Series, Inst. Comput. Sci., Univ. Würzburg, Würzburg, Germany, Res. Rep. 137, Feb.

1996.

[26] LAMPERTI J.W., Semi-Stable Stochastic Processes, Trans. on Am. Math. Soc., 104, pp. 62-78, 1962.

[27] VERVAAT W., Properties of General Self-Similar Processes, Bull. Int. Statist.

Inst., 52, pp. 199-216, 1987.

[28] VERVAAT W., Sample Path Properties of Self-Similar Processes with Stationary Increments, Ann. Probab., 13, pp. 1-27, 1985.

[29] SINAI Y.G., Self-Similar Probability Distributions, Theory Probab. Appl., 21, pp. 64-80, 1976.

[30] BERAN J., Statistics for Long-Memory Processes, London, U.K., Chapman &

Hall, 1994.

[31] PRIESTLEY M.B., Spectral Analysis of Time Series, Academic Press, London, 1981.

[32] PESQUET-POPESCU B. e VEHEL J.L., Stochastic Fractal Models for Image Processing, Signal Processing Magazine, IEEE Vol. 19, pp. 48-62, Sep. 2002.

[33] REED J.C., LEE P.C. e TRUONG T.K., Spectral Representation of fractional Brownian motion in N Dimensions and its Properties, IEEE Trans. on Information Theory, Vol. IT-41, pp. 1439-1451, Sep. 1995.

[34] PESQUET-POPESCU B. e LARZABALE P., 2D Self-Similar Processes with Stationary Fractional Increments in Fractals Engineering, J. Lévy Véhel, E. Lutton, and C. Tricot, Eds. Heidelberg, Germany, Springer-Verlag, pp. 138-151, 1997.

[35] PESQUET-POPESCU B., Wavelet Packet Analysis of 2D Processes with Stationary Fractional Increments, IEEE Trans. on Information Theory, Vol. 45, pp.

1033-1038, 1999.

[36] MATHERON G., Kriging, or Polynomial Interpolation Procedures, Can.

Mining Metallurgical Bull., Vol. 60, pp. 1041-1045, 1967.

[37] BERAN J., Fitting Long-Memory Models by Generalized Linear Regression, Biometrika, Vol. 80, pp. 817-822, 1993.

(3)

Bibliografia

144

[38] BERTACCA M., et al., A FARIMA-Based Analysis for Wind Falls and Oil Slicks Discrimination in Sea SAR Imagery, Proc. IGARSS 2004, Anchorage, Alaska, Vol. 7, pp. 4703-4706.

[39] ILOW J. e LEUNG H., Self-Similar Texture Modeling Using FARIMA Processes with Applications to Satellite Images, IEEE Trans. on Image Processing, Vol. 10, May 2001.

[40] BERIZZI F. e DALLE MESE E., Sea-Wave Fractal Spectrum for SAR Remote Sensing, IEEE Proc. On Radar, Sonar and Navigation, Vol. 148, pp. 56-66, Apr.

2001.

[41] PIERSON W.J. e MOSKOWITZ L., A Proposed Spectral Form for Fully Developed Wind Seas Based on the Similarity Theory of S.A. Kitaigorodskii, Journal of Geophisical Research, Vol. 69, Dec. 1964.

[42] ALPERS W.R. e BRUENING C., On the Relative Importance of Motion- Related Contributions to the SAR Imaging Mechanism of Ocean Surface Waves, IEEE Trans. on Geoscience and Remote Sensing, Vol. GE-24, pp. 873-884, 1986.

[43] LYZENGA D.R., Unconstrained Inversion of Waveheight Spectra from SAR Images, IEEE Trans. on Geoscience and Remote Sensing, Vol. 40, pp. 261-270, Feb.

2002.

[44] DATCU M., Model for SAR Images, Int. Symposium on Optical Engineering and Photonics in Aerospace Sensing, SPIE, 1992.

[45] STEWART C.V., et al.., Fractional Brownian motion Models for Synthetic Aperture Radar Imagery Scene Segmentation, Proceedings of the IEEE, Vol. 81, pp.

1511-1522, Oct. 1993.

[46] FLANDRIN P., On the Spectrum of fractional Brownian motion, IEEE Trans.

on Information Theory, Vol. 35, pp. 197-199, Jan. 1989.

[47] BERTACCA M., BERIZZI F. e DALLE MESE E., A FARIMA Based Technique for Oil Slick and Low Wind Areas Discrimination in Sea SAR Imagery, IEEE Trans. on Geoscience and Remote Sensing, Vol. 43, pp. 2484-2493, Nov. 2005.

[48] FALCONER K., Fractal Geometry, John Wiley & Sons, 1990.

[49] DALLE MESE E., et al., One Dimensional Fractal Model of the Sea Surface, Technical Report FCTL3, Oct. 1996.

[50] VESEKY J.F. e STEWART R.H., The Observation of Ocean Surface Phenomena Using Imagery from the Seasat Synthetic Aperture Radar: an Assessment, Journal of Geophysical Research, Vol. 87, pp. 3397-3430, 1982.

[51] DALLE MESE E., et al., Two Dimensional Fractal Model of the Sea Surface, Technical Report FCTL4, Oct. 1996.

[52] BERTACCA M., BERIZZI F. e DALLE MESE E., FEXP Models for Oil Slick and Low-Wind Areas Analysis and Discrimination in Sea SAR Images, submitted to SEASAR 2006, International workshop on “Advances in SAR Oceanography from ENVISAT and ERS missions,” ESA-ESRIN, Frascati, Roma (Italy), Jan. 2006.

[53] BERTACCA M., et al., Development and Validation of a Sea Surface Fractal Model: Project Results and New Perspective, Envisat symposium, Salzburg (Austria), Sep. 2004.

[54] CAPRIA A., Modelizzazione Frattale di Immagini SAR del Mare, Tesi di Laurea Specialistica in Ingegneria delle Telecomunicazioni, 2003.

[55] BERTACCA M., Analisi Spettrale delle immagini SAR della superficie marina per la discriminazione delle anomalie di superficie, Dottorato di Ricerca in “Metodi e Tecnologie per il Monitoraggio Ambientale”, 2005.

Riferimenti

Documenti correlati

Lo studio dei rapporti tra contesti e dinamiche di apprendimento e uso delle lingue è un campo vastissimo con una bibliografia sterminata. In questo saggio non si tenterà di dare

Given a time horizon, an estimation of the potential demand for the miniliner transport service and a homogeneous fleet of aircraft, the optimization problem consists in finding

Traendo spunto dall’innegabile e crescente suc- cesso delle MH, si è cercato di metterne a fuoco la de- clinazione più adeguata a raggiungere l’obiettivo del- la promozione di

The aims of this study were to investigate the fungal communities of two Alpine experimental sites cultivated with saffron, and to rank the relative impact of two AMF inocula,

Sjögren’s syndrome (SS) and autoimmune thyroid diseases (AITD) may frequently coexist in clinical practice, resulting in a complex overlapping disorder that represents a partic-

Sensing and reporting operations occur when data collection utility and smartphone sensing potential are greater than a threshold δ, which means that the mobile devices sustain a

1000 campioni relativi specificatamente a terreni destinati o destinabili alla coltivazione dei frutti di bosco e forniri da una cooperativa di produttori (S.Orsola)

la specie più allevata è la trota iridea destinata soprattutto al consumo alimentare, seguita a distanza dalla trota fario utilizzata preva- lentemente per il ripopolamento dei