AG2413 Digital Image Processing and Applications

LATEST NEWS	The lecture on Thursday, April 28th is postponed to a later date!
Course Examiner	Professor Yifang Ban, yifang@kth.se
Lecturers	Yifang Ban Helén Rost, BLOM Susanne Kratzer, SU Sara Wiman, Metria
Teaching Assistant	Jan Haas jhaas@abe.kth.se
Literature	Jensen, J.R., 2005. Introductory Digital Image Processing: A Remote Sensing Perspective, 3rd edition, Prentice Hall, Upper Saddle River, New Jersey. 526 pp.
Prerequisites	AG1321, Remote Sensing Technology, 7.5c or equivalent

Course Description

This course aims to provide every student with a working knowledge of sophisticated methods and techniques for collecting, processing and analysing remotely sensed data; as well as the theory and practice of undertaking remote sensing projects. Throughout the course, emphasis will be placed on image processing, image analysis, image classification, remote sensing and GIS data integration, and applications of remote sensing in geographical analysis and environmental monitoring. The course is composed of lectures, laboratory exercises and student presentations.

Change Detection of Urban Growth. Click the image for larger view.

Laboratory Sessions During laboratory sessions, you will have the opportunity to improve your skills on digital image processing and analysis, as well as to conduct a remote sensing project. All meetings of the lab groups are held weekly in the GEO-Lab using PCI Geomatica image processing and analysis software. Students who work two in a group should submit one group report for each lab/project. Student Presentations One of the requirements for this course is to present a remote sensing project to the class. More details will be published soon. Evaluation Exam/Project grading: A-F Lab grading: Pass or redo Please note: 1. All labs have a deadline. If not specified differently in the lab instructions, the due date is always one week after the lab session. Labs are to be uploaded to the Bilda system before the deadline to not forfeit the chance for bonus points. 6 bonus points (1 for each lab) towards the the final grade will be given to students who submit their lab reports and project reports on time. 2. Please observe KTH’s guidelines on academic honesty.

___________________________________________________________________________ Lecture Schedule   (Schedule may change)
Date / Time	Place	Lecture Topic	Required Reading
Tue, Mar 22 10-12	L41	Introduction The Remote Sensing Process Image statistics Remote Sensing Project examples	Jensen Ch 1 Jensen Ch 4 Jensen Ch 7
Tue, Mar 29 10-12	L44	Remote Sensing Data/In situ Data Image Pre-Processing Satellite Orthorectification Geometric Correction Radiometric Correction	Jensen Ch 4 Jensen Ch 7
Mon, Apr 4 10-12	L44	Hyperspectral Sensing & Image Processing	Jensen Ch 6 Jensen Ch 11
Wed, Apr 6 10-12	L44	Image Enhancement & Transformations RGB to IHS Transformation Principal Component Analysis Image Transformations	Jensen Ch 5 Jensen Ch 8
Tue, Apr 12 10-12	L42	LiDAR Processing & Applications Guest lecture Helén Rost	Lecture Notes
TBA TBA	TBA	Radar Remote Sensing: Principles and Applications	Lecture Notes
Wed, May 4 10-12	L42	Image Classification: Advanced Algorithms	Jensen Ch 9 & 10
Mon, May 9 10-12	L43	Digital Change Detection	Jensen Ch 12
Wed, May 11 10-12	L41	Remote Sensing Applications in Marine Environments Guest lecture Susanne Kratzer
Mon, May 16 10-12	L44	Remote Sensing Projects at Metria Guest lecture Sara Wiman
Tue, May 24 9-12	L31	Final Project Presentations