RRY025 RRY025 Image processing lp1 HT23 (7.5 hp)
Course is offered by the department of Space, Earth and Environment
Jouni Kainulainen email@example.com
Jouni Kainulainen firstname.lastname@example.org
Matthias Maercker email@example.com
The aim of this course is for students to become familiar with a wide variety of techniques in modern Image Processing. These techniques can be used to subjectively improve image quality for the end-user (image enhancement), remove known image distortions (image restoration) and to reduce image data sizes for storage or transmission (image compression). These techniques are valuable in a range of applications and careers including, but not limited to, medical imaging, astronomy, remote sensing, automation etc. Emphasis is placed on understanding of the principles, and on application, of the techniques rather than learning of algorithms.
'Digital Image Processing' 3rd edition (2008) by Gonzalez and Woods, or
'Digital Image Processing' 4th edition (2018) by Gonzalez and Woods.
Copies are available to purchase at the Chalmers bookstore. The book is not mandatory, but sections of it are referred to as complementary reading.
The course consists of lectures, in-class exercise/problem sessions, a project, and a written exam. The project and written exam are evaluated and they are mandatory parts of the assessment.
There are typically three two-hour classes per week. These classes are a mixture of lecturing and in-class exercises/demos/problem solving. There will be a two-hour problem consultation session on Thursday afternoons, during which students can meet the teachers to discuss problems and/or, do problems, or work on their project.
Changes made since the last occasion
Learning objectives and syllabus
- Visualise via means of mental images the process of forming 1D and 2D Fourier transforms and also the convolution process. Describe the similarities and differences between the continuous and discrete Fourier transforms and their inter-relationship.
- Select and apply appropriate image enhancement methods for different applications. Discriminate between cases where automated image enhancement methods produce appropriate results and where they do not.
- Understand the differences between averaging and median filtering for reducing image noise.
- Demonstrate understanding of image smoothing and sharpening in both the image and Fourier domains. Select between optimum methods of edge detection in different applications.
- Describe common distorted images as convolutions of the true image with point spread functions (PSF). Describe and decide under which conditions different image restoration algorithms can be used and describe the strengths and weakness of these algorithms.
- Describe the Cosine transform and its relationship to the Fourier transform.
- Demonstrate a basic understanding of wavelets and know how to use them to compress and denoise data.
- Explain the difference between lossy and lossless compression methods and explain the concept of data redundancy as the source of compression. Describe the subcomponents of general compressor/decompressor algorithms. Calculate theoretical limits to lossless compression using the Shannon noiseless coding theorem and implement Huffman coding.
- Describe a variety of different mapping functions that can be used to obtain compression and decide when different methods are appropriate. Show via examples why Digital Pulse Code Modulation (DPCM) works and is stable in the face of quantisation errors.
- Describe the main components of the JPEG standard.
- Write computer code in MATLAB to implement selected image processing algorithms.
Link to the syllabus on Studieportalen.
Most course points are allocated via a traditional written exam at the end of the course, 75% of course points are given via the written exam. In order to pass the course a project must be executed, a report written and handed in. 25% of the total course points are based on the grade given to the project work. Instructions on the project work including the hand-in date for the project report are given under the Project Module. The written exam will be held on the afternoon of 27th October.
The final grade depends on this sum of points for the written exam (out of 30pts) and the project (out of 10 pts). The Grade boundaries will be
Total Points (exam + project)
Grade 3 19.0 - 25.49
Grade 4 25.5 - 31.99
Grade 5 32.0 – 40.0
The rules for aids during the exam are:
Calculators (of Chalmers approved type) are allowed. Laptops, tablets etc are not allowed. Mobile phones cannot be used during the exam. It is allowed to bring one A4 sheet of self-written notes to the exam. An English-Swedish Dictionary can be brought into the exam. No other written or printed material can be brought into the exam. Questions can be answered in English or Swedish (English is recommended, but the language choice does not affect grading). Jouni and Matthias try to visit the exam room twice to resolve any queries about the questions, once about 90 minutes after the start and then 3 hours after the start.
The syllabus page shows a table-oriented view of course schedule and basics of course grading. You can add any other comments, notes or thoughts you have about the course structure, course policies or anything else.
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