1·在國(guó)防科學(xué)技術(shù)領(lǐng)域中,學(xué)術(shù)水平高,內(nèi)容有創(chuàng)見,在學(xué)科上居領(lǐng)先地位的基礎(chǔ)科學(xué)理論圖書;在工程技術(shù)理論方面有突破的應(yīng)用科學(xué)專著。
2·學(xué)術(shù)思想新穎,內(nèi)容具體、實(shí)用,對(duì)國(guó)防科技和武器裝備發(fā)展具有較大推動(dòng)作用的專著;密切結(jié)合國(guó)防現(xiàn)代化和武器裝備現(xiàn)代化需要的高新技術(shù)內(nèi)容的專著。
3·有重要發(fā)展前景和有重大開拓使用價(jià)值,密切結(jié)合國(guó)防現(xiàn)代化和武器裝備現(xiàn)代化需要的新工藝、新材料內(nèi)容的專著。
4·填補(bǔ)目前我國(guó)科技領(lǐng)域空白并具有軍事應(yīng)用前景的薄弱學(xué)科和邊緣學(xué)科技圖書。
Chapter 1 OVerview for Statistical Modeling of SAR Images
1.1 Introduction
1.2 Model Classification and Research Contents
1.2.1 Parameter estimation
1.2.2 Goodness—of-fit tests
1.3 Statistical models
1.3.1 Nonparametric models
1.3.2 Parametric models
1.4 Classification of parametric models
1.4.1 The statistical models developed from the product model
1.4.2 The statistical models developed from the generalized centrallimit theorem
1.4.3 The empirical distributions
1.4.4 Other models
1.5 The Relationship Among The Major Models and TheirApplications
1.5.1 The relationship among the parametric statisticalmodels
Chapter 1 OVerview for Statistical Modeling of SAR Images
1.1 Introduction
1.2 Model Classification and Research Contents
1.2.1 Parameter estimation
1.2.2 Goodness—of-fit tests
1.3 Statistical models
1.3.1 Nonparametric models
1.3.2 Parametric models
1.4 Classification of parametric models
1.4.1 The statistical models developed from the product model
1.4.2 The statistical models developed from the generalized centrallimit theorem
1.4.3 The empirical distributions
1.4.4 Other models
1.5 The Relationship Among The Major Models and TheirApplications
1.5.1 The relationship among the parametric statisticalmodels
1.5.2 Summary of the applications of the major models
1.6 Discussion of Future Work
1.7 Conclusions References
Chapter 2 Statistical Modeling of Single-Channel SAIl IInages
2.1 Modeling SAR Images Based on A Generalized Gamma Distributionfor Texture Component
2.1.1 The Proposed GFFodel
2.1.2 Parameter Estimator of the GFF Model Based on MoLC
2.1.3 ExperimentaI Results
2.1.4 Appendix 2-A.The Derivation of m-th order moments of theDistribution
2.1.5 Appendix 2-B.Proof of the relationship betweenDistributions
2.2 An Empirical Distribution for Characterizing the StatisticalProperties of SAR Clutter
2.2.1 The Proposed Distribution
2.2.2 The Parameter Estimators of The Proposed Distribution
2.2.3 Experimental Results
……
Chapter 4 Statistical Modeling of Multi-Channel SAR images
Chapter 5 Target Detwction Multi-Channel SAR Images
Chapter 6 Statistical Modeling and Target Detwction of PolSARImages