Digital Image Processing (summer term 2017)

Dr. Christian Melsheimer (room SpT C3165, tel. -62181)

Dr. Gunnar Spreen (room SpT C3170, tel. -62180)

Thursday, 8:15 - 11:00 (exercises and lecture), room S3032 (PEP room)

Announcements

Abstract

In environmental physics and remote sensing one often has to deal with two- or multidimensional data: For example, a satellite image taken at one single frequency, is two-dimensional, an image taken at several frequencies - a multi- or hyperspectral image - is three-dimensional, the third dimension being the frequency; likewise, time could be the third frequency if the same area is imaged repeatedly.

Here we want to understand and learn to use the tools for displaying such data as, e.g., grey-scale or colour images and for extracting information from them. This involves basic image processing techniques like contrast enhancement, geometrical transformations, filtering, segmentation and classification, and methods like principal component analysis.

Contents of the Lecture (with links to some lecture notes)
  1. (13 Apr 2017) Basics: digital image, histogram, grey-level transformation
  2. (20 April 2017) Linear (convolution) filters: differential filters. Additionally: Color images
  3. (27 April 2017) Color images (rest); Geometrical operations/transformation
  4. (4 May 2017) Segmentation (finding objects)
  5. (11 May 2017) Segmentation: Morphological Filters, Connected components (see lecture notes of lecture #4); Feature extraction (characterizing objects)
  6. (18 May 2017) Classification
  7. (1 June 2017) Principal component analysis (PCA)
  8. (8 June 2017) Fourier Transformation, Linear filters in the frequency domain
  9. (15 June 2017) Linear filters in the frequency domain (see lecture notes of previous week), Sampling theorem (no lecture notes available).
  10. (22 June 2017) Image coding and compressionn
  11. (29 June 2017) Image Restoration

Exercises

There will be about one set of exercises (2 to 4 problems) each week. Please submit your exercises by by Wednesday noon 12:00 CEST - that's one day before the next lecture.

You can either submit a PDF file by email, or put a paper version in the basket labeled "Exercises Digital Image Processing" which we will place in the PEP computer room S3031 in (in front of the PEP seminar room S3032).

The exercises will then be discussed on the next lecture day (Thursday 8:15), before the lecture.

In order to successfully pass the course, you have to solve at least 50% of the exercises problems and do the oral exam

  1. 1st set of problems, 13 Apr 2017. Submit until Wednesday, 19 April, 12:00 noon.
  2. 2nd set of problems, 20 April 2017. Submit until 26 Apr, 12:00. Here is an Image of Bremen to be used with Problem 6.
  3. 3rd set of problems, 27 April 2017. Submit until 3 May, 12:00. Here is a colour image of Bremen to be used with Problem 10.
  4. 4th set of problems, 4 May 2017. Submit until 10 May, 12:00 CEST
  5. 5th set of problems, 11 May, 2017. Submit until 17 May.
  6. 6th set of problems. 19 May, 2017, submit until 31 May, 12:00. Matlab file with the matrix to be used for problem 20
  7. 7th set of problems, 1 June, 2017. Submit until 7 June.
  8. 8th set of problems, 8 June, 2017. Submit until 14 June.
  9. 9th set of problems, 15 June, 2017. Submit until 21 June.
  10. 10th set of problems, 22 June, 2017. Submit by 28 June, 12:00 CEST. Here are the three images you need for it: Test image 1, Test image 2, Test image 3 (note: the first two were copied from the German wikipedia article about Bremen).
  11. 11th set of problems, 28 June 2017. Subit by 5 July.

Miscellaneous

Exam

There will be an oral exam after the lectures have finished. First time window: July 24 to August 4, or later in August or September. Exact date to be agreed upon individually.

Bibliography

There are many books on that subject, here is a selection:

  1. K. R. Castleman: Digital Image Processing. Prentice Hall, Englewood Cliffs, 1996.
  2. R. C. Gonzalez, R. E. Woods: Digital Image Processing. Addison-Wesley, Second Edition, 2002.
  3. B. Jähne: Digital Image Processing. Springer, 2002.
  4. T.M. Lillesand, R.W. Kiefer: Remote Sensing and Image Interpretation. Wiley, 2000.
  5. J.C. Russ: The Image Processing Handbook, 5th Edision. CRC Press, 2006 (ISBN 0-8493-7254-2).
  6. R. A. Schowengerdt: Remote Sensing, Models and Methods for Image Processing. Academic Press, 1997.
C. Melsheimer, Last modified: Thu Jun 22 10:00:58 CEST 2017