Remote Sensing Digital Image Analysis

1 - Sources and Characteristics of Remote Sensing Image Data.- 2 - Error Correction and Registration of Image Data.- 3 -The Interpretation of Digital Image Data.- 4 - Radiometric Enhancement Techniques.- 5 - Geometric Enhancement Using Image Domain Techniques.- 6 - Multispectral Transformations of Image Data.- 7 - Fourier Transformation of Image Data.- 8 - Supervised Classification Techniques.- 9 - Clustering and Unsupervised Classification.- 10 - Feature Reduction.- 11 - Image Classification Methodologies.- 12 - Data Fusion.- 13 - Interpretation of Hyperspectral Image Data.- Appendix A - Satellite Altitudes and Periods.- References for Appendix A.- Appendix B - Binary Representation of Decimal Numbers.- Appendix C - Essential Results from Vector and Matrix Algebra.- C.1 Definition of a Vector and a Matrix.- C.2 Properties of Matrices.- C.3 Multiplication, Addition and Subtraction of Matrices.- C.4 The Eigenvalues and Eigenvectors of a Matrix.- C.5 Some Important Matrix, Vector Operations.- C.6 An Orthogonal Matrix - the Concept of Matrix Transpose.- C.7 Diagonalisation of a Matrix.- References for Appendix C.- Appendix D - Some Fundamental Material from Probability and Statistics.- D.1 Conditional Probability.- D.2 The Normal Probability Distribution.- D.2.1 The Univariate Case.- D.2.2 The Multivariate Case.- References for Appendix D.- Appendix E - Penalty Function Derivation of the Maximum Likelihood Decision Rule.- E.1 Loss Functions and Conditional Average Loss.- E.2 A Particular Loss Function.- References for Appendix E.