Image analysis, classification and change detection in remote sensing : with algorithms for for ENVI/IDL and Python /: with algorithms for for ENVI/IDL and Python. (2014)
- Record Type:
- Book
- Title:
- Image analysis, classification and change detection in remote sensing : with algorithms for for ENVI/IDL and Python /: with algorithms for for ENVI/IDL and Python. (2014)
- Main Title:
- Image analysis, classification and change detection in remote sensing : with algorithms for for ENVI/IDL and Python
- Further Information:
- Note: Morton J. Canty.
- Authors:
- Canty, Morton John
- Contents:
- 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; SimpleImages, 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; … (more)
- Edition:
- Third edition
- Publisher Details:
- Boca Raton : CRC Press
- Publication Date:
- 2014
- Extent:
- 1 online resource, illustrations (black and white)
- Subjects:
- 621.3670285
Remote sensing -- Mathematics
Image analysis -- Mathematics - Languages:
- English
- ISBNs:
- 9781466570382
9781466570399 - Related ISBNs:
- 9781466570375
- Notes:
- Note: Includes bibliographical references and index.
Note: Description based on CIP data; item not viewed. - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.140337
- Ingest File:
- 02_159.xml