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CZECH TECHNICAL UNIVERSITY IN PRAGUE
STUDY PLANS
2023/2024

Digital Processing of Remote Sensing Data

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Code Completion Credits Range Language
D55DPZ_EN ZK 2P English
Garant předmětu:
Lena Halounová
Lecturer:
Lena Halounová
Tutor:
Supervisor:
Department of Geomatics
Synopsis:

The course is focused on classical and new methods of image processing. In addition to the classical remote sensing procedures in terms of digital image analysis and classification (controlled and uncontrolled classification, symptoms and diminishing the size of the data set, classification classification success), new textural, hyperspectral and radar image processing procedures are taken into account. An important part is the interconnection of teaching with GIS, photogrammetry and remote sensing, also the methods of filtration with regard to DMT, rectification and orthogonalization of VHR satellite data as well as the search for partial primitives about image associated with programming are innovated.

Requirements:
Syllabus of lectures:
Syllabus of tutorials:
Study Objective:
Study materials:

Základní literatura:

[1] Sonka, M., Hlavac, V., Boyle, R.: Image Processing, Analysis, and Machine Vision. 1999. PWS Publishing, 2nd edition.

[2] Richards, John A. Remote Sensing Digital Image Analysis, 5th ed. 2013, XIX, 494 pp.

[3] Soergel, Uwe (Ed.).Series: Radar Remote Sensing of Urban Areas, Vol. 15, 2010

[4] Canty, Morton J.: Image Analysis, classification and change detection in remote sensing. 2007. Taylor & Francis, ISBN 0-8493-7251-8.

Doporučená literatura:

[5] Castleman, K. R.: Digital Image Processing. Pearson, 1995. ISBN-13: 978-0132114677

[6] Manual of eCognition trial Software, Trimble, http://www.ecognition.com/free-trial.

[7] Manual of PCI software. PCI Enterprises, 50 West Wilmot Street, Unit 200E, Richmond Hill, Ontario, Canada, 2017.

Note:
Time-table for winter semester 2023/2024:
Time-table is not available yet
Time-table for summer semester 2023/2024:
Time-table is not available yet
The course is a part of the following study plans:
Data valid to 2024-03-16
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