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Change detection and image time-series analysis. (Record no. 69732)

000 -LEADER
fixed length control field 04613cam a2200505Ia 4500
001 - CONTROL NUMBER
control field on1288211836
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20220711203738.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 211211s2022 enk o 000 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119882268
-- (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119882265
-- (electronic bk. : oBook)
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 9781119882244
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
ISBN 1119882249
029 1# - (OCLC)
OCLC library identifier AU@
System control number 000070461791
082 04 - CLASSIFICATION NUMBER
Call Number 519.5/5
245 00 - TITLE STATEMENT
Title Change detection and image time-series analysis.
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication London, UK :
Publisher ISTE, Ltd. ;
Place of publication Hoboken, NJ :
Publisher Wiley,
Year of publication 2022.
300 ## - PHYSICAL DESCRIPTION
Number of Pages 1 online resource (304 p.)
490 0# - SERIES STATEMENT
Series statement Image. Remote sensing imagery
500 ## - GENERAL NOTE
Remark 1 Description based upon print version of record.
505 0# - FORMATTED CONTENTS NOTE
Remark 2 Cover -- Half-Title Page -- Title Page -- Copyright Page -- Contents -- Preface -- List of Notations -- Chapter 1. Unsupervised Change Detection in Multitemporal Remote Sensing Images -- 1.1. Introduction -- 1.2. Unsupervised change detection in multispectral images -- 1.2.1. Related concepts -- 1.2.2. Open issues and challenges -- 1.2.3. Spectral-spatial unsupervised CD techniques -- 1.3. Unsupervised multiclass change detection approaches based on modeling spectral-spatial information -- 1.3.1. Sequential spectral change vector analysis (S2CVA)
505 8# - FORMATTED CONTENTS NOTE
Remark 2 1.3.2. Multiscale morphological compressed change vector analysis -- 1.3.3. Superpixel-level compressed change vector analysis -- 1.4. Dataset description and experimental setup -- 1.4.1. Dataset description -- 1.4.2. Experimental setup -- 1.5. Results and discussion -- 1.5.1. Results on the Xuzhou dataset -- 1.5.2. Results on the Indonesia tsunami dataset -- 1.6. Conclusion -- 1.7. Acknowledgements -- 1.8. References -- Chapter 2. Change Detection inTime Series of Polarimetric SAR Images -- 2.1. Introduction -- 2.1.1. The problem
505 8# - FORMATTED CONTENTS NOTE
Remark 2 2.1.2. Important concepts illustrated bymeans of the gamma distribution -- 2.2. Test theory and matrix ordering -- 2.2.1. Test for equality of two complex Wishart distributions -- 2.2.2. Test for equality of k-complex Wishart distributions -- 2.2.3. The block diagonal case -- 2.2.4. The Loewner order -- 2.3. The basic change detection algorithm -- 2.4. Applications -- 2.4.1. Visualizing changes -- 2.4.2. Fieldwise change detection -- 2.4.3. Directional changes using the Loewner ordering -- 2.4.4. Software availability -- 2.5. References
505 8# - FORMATTED CONTENTS NOTE
Remark 2 Chapter 3. An Overview of Covariance-based Change Detection Methodologies in Multivariate SAR Image Time Series -- 3.1. Introduction -- 3.2. Dataset description -- 3.3. Statistical modeling of SAR images -- 3.3.1. The data -- 3.3.2. Gaussian model -- 3.3.3. Non-Gaussian modeling -- 3.4. Dissimilarity measures -- 3.4.1. Problem formulation -- 3.4.2. Hypothesis testing statistics -- 3.4.3. Information-theoretic measures -- 3.4.4. Riemannian geometry distances -- 3.4.5. Optimal transport -- 3.4.6. Summary -- 3.4.7. Results of change detectors on the UAVSAR dataset
505 8# - FORMATTED CONTENTS NOTE
Remark 2 3.5. Change detection based on structured covariances -- 3.5.1. Low-rank Gaussian change detector -- 3.5.2. Low-rank compound Gaussian change detector -- 3.5.3. Results of low-rank change detectors on the UAVSAR dataset -- 3.6. Conclusion -- 3.7. References -- Chapter 4. Unsupervised Functional Information Clustering in Extreme Environments from Filter Banks and Relative Entropy -- 4.1. Introduction -- 4.2. Parametric modeling of convnet features -- 4.3. Anomaly detection in image time series -- 4.4. Functional image time series clustering -- 4.5. Conclusion -- 4.6. References
500 ## - GENERAL NOTE
Remark 1 Chapter 5. Thresholds and Distances to Better Detect Wet Snow over Mountains with Sentinel-1 Image Time Series.
700 1# - AUTHOR 2
Author 2 Atto, Abdourrahmane M.
700 1# - AUTHOR 2
Author 2 Bovolo, Francesca.
700 1# - AUTHOR 2
Author 2 Bruzzone, Lorenzo.
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier https://doi.org/10.1002/9781119882268
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1
-- Time-series analysis.
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-- 92
-- DG1

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