Image Analysis, Classification and Change Detection in Remote Sensing
Crc Press Inc (Verlag)
978-1-4665-7037-5 (ISBN)
- Titel erscheint in neuer Auflage
- Artikel merken
See What’s New in the Third Edition:
Inclusion of extensive code in Python, with a cloud computing example
New material on synthetic aperture radar (SAR) data analysis
New illustrations in all chapters
Extended theoretical development
The material is self-contained and illustrated with many programming examples in IDL. The illustrations and applications in the text can be plugged in to the ENVI system in a completely transparent fashion and used immediately both for study and for processing of real imagery. The inclusion of Python-coded versions of the main image analysis algorithms discussed make it accessible to students and teachers without expensive ENVI/IDL licenses. Furthermore, Python platforms can take advantage of new cloud services that essentially provide unlimited computational power.
The book covers both multispectral and polarimetric radar image analysis techniques in a way that makes both the differences and parallels clear and emphasizes the importance of choosing appropriate statistical methods. Each chapter concludes with exercises, some of which are small programming projects, intended to illustrate or justify the foregoing development, making this self-contained text ideal for self-study or classroom use.
Images, Arrays, and Matrices
Multispectral satellite images
Synthetic aperture radar images
Algebra of vectors and matrices
Eigenvalues and eigenvectors
Singular value decomposition
Finding minima and maxima
Exercises
Image Statistics
Random variables
Parameter estimation
Multivariate distributions
Bayes’ Theorem, likelihood and classification
Hypothesis testing
Ordinary linear regression
Entropy and information
Exercises
Transformations
The discrete Fourier transform
The discrete wavelet transform
Principal components
Minimum noise fraction
Spatial correlation
Exercises
Filters, Kernels and Fields
The Convolution Theorem
Linear filters
Wavelets and filter banks
Kernel methods
Gibbs–Markov random fields
Exercises
Image Enhancement and Correction
Lookup tables and histogram functions
High-pass spatial filtering and feature extraction
Panchromatic sharpening
Radiometric correction of polarimetric SAR imagery
Topographic correction
Image–image registration
Exercises
Supervised Classification Part
Maximizing the a posteriori probability
Training data and separability
Maximum likelihood classification
Gaussian kernel classification
Neural networks
Support vector machines
Exercises
Supervised Classification Part
Postprocessing
Evaluation and comparison of classification accuracy
Adaptive boosting
Classification of polarimetric SAR imagery
Hyperspectral image analysis
Exercises
Unsupervised Classification
Simple cost functions
Algorithms that minimize the simple cost functions
Gaussian mixture clustering
Including spatial information
A benchmark
The Kohonen self-organizing map
Image segmentation
Exercises
Change Detection
Algebraic methods
Postclassification comparison
Principal components analysis (PCA)
Multivariate alteration detection (MAD)
Decision thresholds
Unsupervised change classification
Change detection with polarimetric SAR imagery
Radiometric normalization of multispectral imagery
Exercises
A Mathematical Tools
B Efficient Neural Network Training Algorithms
C ENVI Extensions in IDL
D Python Scripts
Mathematical Notation
References
Index
| Zusatzinfo | 20 page follows page 230; 143 Illustrations, black and white |
|---|---|
| Verlagsort | Bosa Roca |
| Sprache | englisch |
| Maße | 156 x 235 mm |
| Gewicht | 953 g |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Naturwissenschaften ► Geowissenschaften ► Geografie / Kartografie | |
| Technik | |
| ISBN-10 | 1-4665-7037-7 / 1466570377 |
| ISBN-13 | 978-1-4665-7037-5 / 9781466570375 |
| Zustand | Neuware |
| Haben Sie eine Frage zum Produkt? |
aus dem Bereich
