Course Catalog 2011-2012
SGN-3057 Digital Image Processing II, 6 cr
Suitable for postgraduate studies
Pavlo Molchanov, Artem Migukin, Karen Eguiazarian, Matteo Maggioni
|Study type||P1||P2||P3||P4||Summer||Implementations||Lecture times and places|
50% attendance at lectures is required. At least 30% of classroom-exercise tasks and 3 assignments.
Principles and baselines related to teaching and learning
Students get in-depth view of selected topics of image processing and perform practical tasks in image processing laboratory.
|Content||Core content||Complementary knowledge||Specialist knowledge|
|2.||Image data compression.|
|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.
Numerical evaluation scale (1-5) will be used on the course
|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
More precise information per implementation
|Implementation||Description||Methods of instruction||Implementation|