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Course Catalog 2011-2012
SGN-3057 Digital Image Processing II, 6 cr |
Additional information
Suitable for postgraduate studies
Person responsible
Pavlo Molchanov, Artem Migukin, Karen Eguiazarian, Matteo Maggioni
Lessons
Study type | P1 | P2 | P3 | P4 | Summer | Implementations | Lecture times and places |
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Requirements
50% attendance at lectures is required. At least 30% of classroom-exercise tasks and 3 assignments.
Principles and baselines related to teaching and learning
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Learning outcomes
Students get in-depth view of selected topics of image processing and perform practical tasks in image processing laboratory.
Content
Content | Core content | Complementary knowledge | Specialist knowledge |
1. | Image representation. | ||
2. | Image data compression. | ||
3. | Object recognition. | ||
4. | Image filtering, segmentation and restoration. | ||
5. | Practical image processing tasks. |
Evaluation criteria for the course
Course grade is computed based on four units as follows: Classroom exercises, 40% of the mark. First laboratory work, 10% of the mark. Second laboratory work, 20% of the mark. Third laboratory work, 30% of the mark All four units must be passed otherwise final mark is not given. There is no exam.
Assessment scale:
Numerical evaluation scale (1-5) will be used on the course
Study material
Type | Name | Author | ISBN | URL | Edition, availability, ... | Examination material | Language |
Book | "Digital Image Processing" | R. Gonzalez and R. Woods | 2nd ed., Prentice-Hall, 2002 | English | |||
Book | "Local Approximation Techniques in Signal and Image Processing" | V.Katkovnik, K.Egiazarian, and J.Astola | 978-0819460929 | English | |||
Book | "The Image Processing Handbook" | John Russ | Fourth Edition, CRC Press, 2002 | English | |||
Book | "The Transform and Data Compression Handbook" | K. Rao and P. Yip | CRC Press, 2001 | English |
Prerequisite relations (Requires logging in to POP)
Correspondence of content
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More precise information per implementation
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