Z8114 Remote sensing digital image processing

Faculty of Science
Autumn 2004
Extent and Intensity
1/2/0. 5 credit(s). Type of Completion: zk (examination).
Teacher(s)
prof. RNDr. Petr Dobrovolný, CSc. (seminar tutor)
Mgr. Kateřina Fárová (seminar tutor)
Guaranteed by
RNDr. Vladimír Herber, CSc.
Department of Geography - Earth Sciences Section - Faculty of Science
Contact Person: prof. RNDr. Petr Dobrovolný, CSc.
Timetable
Mon 14:00–14:50 Z1
  • Timetable of Seminar Groups:
Z8114/01: Wed 8:00–9:50 Z1, K. Fárová
Course Enrolment Limitations
The course is only offered to the students of the study fields the course is directly associated with.
fields of study / plans the course is directly associated with
Course objectives
Hard copy images and digital images. Interpretation of hard copy imagery Principles of visual interpretation, interpretation keys Advantages and drawbags of hard copy imagery and visual interpretation Characteristics of digital imagery. Raster data format and its specific features Remotely sensed data chracter, A- D conversion. Basic types of image resolution Image Data storage. Comonn and specific data formats. Image compression. Auxiliary data. Basic steps of digital image data processing Preprocessing, radiometric and atmospheric corrections. Geometric correction and transformation. Image enhancement, image histogram. Principles of automatic classification. Suppervised and unsuppervised approaches New methods of image classification. Image processing of RADAR and hyperspectral data. Change detection.
Syllabus
  • 1. Basic properties of digital image A-D conversion, DN and its meaning,histogram, multispectral and hyperspectral data, types of vizualization, color spaces, RGB system 2. Preprocessing of digital imagery Radiometric and atmospheric corrections - basic algorithms, geometric correction - overview of common methods(polynomic transformation, splines, TIN, orthocorrection using DEM 3. Image enhancement I. Radiometric (point) enhancements, working with histogram, image contrast, basic types of radiometric enhancements, LUT, density slicing 4. Image enhancement II. Spatial enhancements - image filtering, principles and basic algorithms of high and low pass filtering, Fourier transformation, textural analysis of RADAR images 5. Image enhancements III. Multi band image transformations, color transformations, IHS x RGB, principal component analysis, ratio images, spectral (vegetation) indicies, TASSELED CAP 6. Suppervised image classification I. Spectral signatures and feature space, common approaches, training sites, 7. Suppervised image classification II. Per-pixel classificators - parelellepipeds, minimum distance, maximum likelyhood, spectral signatures and its statistical description and evaluation. Evaluation of image classification - error matrix, test sites. 8. Unsuppervised image classification Spectral and information classes, cluster analysis, ISODATA a K-MEANS, aggregation, postclassification corections 9. New approaches to image classification Fuzzy classification, neural networks, textural and contextual classification kontextuální, SAM, ECHO 10. RADAR data image processing. Specifc features of RADAR imagery, basic algorithms, filtering, textural analysis, examples using RADAR imagery 11. Principles of hyperspectral image analysis. Hyperspectral cube, "mixels" and a "pure" pixels, spectral libraries, endmembers, hyperspectral data classification - unmixing 12. Basic approaches to change detection Ratio images, classification comparison, Change vector analysis, PCA
Literature
  • DOBROVOLNÝ, Petr. Dálkový průzkum Země. Digitální zpracování obrazu. 1. vyd. Brno: Masarykova univerzita, 1998. 208 s. ISBN 8021018127. info
  • LILLESAND, Thomas M. and Ralph W. KIEFER. Remote sensing and image interpretation. 3rd ed. New York: John Wiley & Sons, 1994. xvi, 750. ISBN 0471577839. info
  • CAMPBELL, James B. Introduction to remote sensing. New York: Guilford Press, 1987. xxiv, 551. ISBN 0-89862-776-1. info
Language of instruction
Czech
Further comments (probably available only in Czech)
Study Materials
The course is taught annually.
Listed among pre-requisites of other courses
The course is also listed under the following terms Autumn 2007 - for the purpose of the accreditation, Autumn 2010 - only for the accreditation, Spring 2004, Autumn 2005, Autumn 2006, Autumn 2007, Autumn 2008, Autumn 2009, Autumn 2010, Autumn 2011, Autumn 2011 - acreditation, Autumn 2012, Autumn 2013, Autumn 2014, Autumn 2015, Autumn 2016, autumn 2017, Autumn 2018, Autumn 2019, Autumn 2020.
  • Enrolment Statistics (Autumn 2004, recent)
  • Permalink: https://is.muni.cz/course/sci/autumn2004/Z8114