Lectures: Wednesdays 5:30-7:30 pm in CH 413
Labs: Wednesdays 7:40-9:10 pm in CH 469 or Thursdays 5-7 pm in CH 1
Course URL: http://web.pdx.edu/~jduh/courses/geog481/index.htm
or go to instructor’s webpage (http://web.pdx.edu/~jduh/
) and select “Courses-> GEOG 4/581”
from the pull-down menu.
Instructor:
Email: jduh@pdx.edu
Office: CH 424J
Office hours: 1-3 Mondays and 1-2 Wednesdays
This course teaches the theory and methods of digital image processing. We will explore the principles of image statistics extraction, radiometric and geometric correction, image enhancement, thematic classification, change detection, and integration of satellite imagery and geographic information systems databases. Computer processing of digital satellite images will be a central part of the course. Many different satellite image data sets will be processed using the ERDAS Imagine image processing software package. These data sets include Landsat, SPOT, RadarSat, IRS, IKONOS, EOS AM (Terra), AVHRR, and AVIRIS.
The text for this course is Introductory Digital Image
Processing: A Remote Sensing Perspective (3rd Edition) which was written by John
R. Jenson: 2004, Prentice Hall, ISBN 0-13-1453610 (released on Dec 1st 2003).
The book is available at the Portland State Bookstore and from Amazon.com . The lecture component of this course consists of discussions
of the readings and therefore you should have read the material before class.
Students are expected to come to class ready to be active participants in the
discussion. To facilitate an interactive discussion each student will be a
discussion leader once during the term for which they will receive a grade.
This person is responsible for leading the classroom discussion along with the
instructor and should have answered all of the discussion questions linked to
the schedule below. The discussion leader should give the instructor
typed answers to all of the questions at the beginning of class. It is
important that everyone in the class take part in these discussions. Therefore,
class attendance and participation are mandatory. See the grading section below
for penalties for those who do not attend class. If you must miss class then you need to hand in the
discussion questions for that day. That means that if you miss class on a
particular day then you should give the instructor typed answers to all of the
questions at the beginning of the next class.
The lab will meet in CH 469 (or CH 1 on Thursdays) where you will do practical image processing exercises on the computers. If you do not finish the labs during the assigned time periods the lab also has open hours. The practical exercises provide a way to acquire skills using Erdas Imagine and to apply the course concepts to real data. The Erdas lab manual and Erdas Field Guide are available in Acrobat format.
Lab Assignments 50%
Midterm 15%
Discussion Lead 10%
Participation 10%
Final 15%
Attendance to this course is mandatory. If you miss class then you must hand in
typed answers to all of the discussion questions for that day. This is in
addition to the day you are the discussion leader. So if you miss two
days during the term then you must hand in typed discussion questions for three
days. You are given two free absences. If you miss more than two class
periods then you will be penalized five percent of your final grade per
absence. PLEASE DO NOT MISS CLASS. You are expected to take part in the
discussions and if you are not in class then you cannot. If you are repeatedly
late you will be given an absence.
Schedule of Lectures, Readings, and Labs
|
Week |
Wednesday |
Lab |
|
1 Jan 5 |
· Course Overview, Syllabus · Introduction to digital image processing (Slides) · Lab Introduction |
Lab 1: Image display (Due by 5pm Jan 19) |
|
2 Jan 12 |
· Remote sensing and digital image processing (Chapter 1) · Remote sensing data collection I (Chapter 2 pages 35-95) (Slides) |
Lab 2: Making maps from satellite imagery (Due by 5pm Jan 19) |
|
3 Jan 19 |
· Remote sensing data collection II (Chapter 2 pages 95-106) (Slides) · Image quality Assessment and statistical evaluation (Chapter 4) |
Lab 3: Classification (Due by 5pm Jan 26) |
|
4 Jan 26 |
· Initial display alternatives and scientific visualization (Chapter 5) · Geometric correction (Chapter 7) |
Lab 4: Polynomial rectification (Due by 5pm Feb 2) |
|
5 Feb 2 |
· Electromagnetic radiation principles and radiometric correction (Chapter 6) · Image enhancement I (Chapter 8 pages 255-274) |
Lab 5: Enhancing imagery (Due by 5pm Feb 16) |
|
6 Feb 9 |
· Image enhancement II (Chapter 8 pages 274-301) ·
Midterm exam |
Lab 5 |
|
7 Feb 16 |
· Image enhancement III (Chapter 8 pages 301-336) · Image classification I (Chapter 9 pages 337-370) |
Lab 6: Advanced classification and accuracy assessment (Due by 5pm Mar 2) |
|
8 Feb 23 |
· Image classification II (Chapter 9 pages 370-389) |
Lab 6 |
|
9 Mar 2 |
· Image classification III (Chapter 9 pages 389-401) (Slides) · Accuracy assessment (Chapter 13) |
Lab 7: Radar image processing (Due by 5pm Mar 16) |
|
10 Mar 9 |
· Change detection (Chapter 12) |
Lab 7 |
|
Mar 16 |
· Final exam (Wednesday, 17:30-19:20 CH 413) |
|