SGN-3057 Digital Image Processing II – 2013, 6 cr


Lectures, 32 h., given during 3rd period

First lecture, January 7, 2013, Monday, 12:15 – 14:00, in TB219 and January 9, Wednesday, 14:15 - 16:00, in TB 222

The lectures are given by Karen Egiazarian (karen <dot> egiazarian <at> tut <dot> fi).

Time and place: Mondays at 12:15 – 14:00 in TB 219 and Wednesdays 14:15 – 16:00 in TB 222

 


Classroom exercises, 14h., given during 3rd period

The exercise on 12.02.2013 is cancelled, the next will be on 19.02.2013

Group A: Tuesdays at 12:15 – 13:45, TB 215 (only Jan 15, 12:15 – 14:45 the room is TC131)

Group B: Tuesdays at 16:15 – 17:45, TB 215

 

First exercises are on January 15, 2013, Tuesday, 12:15 – 13:45, TC131 (group A) and 16:15 – 17:45, TB 215 (group b)

 

For more details and weekly assignments, check the classroom exercises webpage. 


Laboratory works, given during 4th period

Check the laboratory work webpage.

Final grades

Here


Additinal tasks for bonus

Check the tasks.

The tasks are not mandatory, however students can solve them for additional bonus to the final grade.



About the course

Goals

·      In-dept view of selected topics of image processing

·      Practical tasks in image processing laboratory

Prerequisites and position

·      Basic or introductory signal processing

·      Digital Image Processing I or Digitaalinen kuvankäsittely I

·      Pre-required for the course Digital Image Processing III

Grade formation

No exam. 

Final mark is computed based on four units as follows:

·      Classroom exercises, 40% of the mark

·      First laboratory work, 20% of the mark

·      Second laboratory work, 20% of the mark

·      Third laboratory work, 20% of the mark

All four units must be passed otherwise final mark is not given


Course schedule

Lecture 1, 07.01.2013 and 09.01.2013

Wavelets and Multiresolution Processing, 4h.

·      Background: image pyramids, subband coding, Haar transform

·      Multiresolution: series expansion, scaling functions, wavelets

·      Fast wavelet transform, Mallat’s algorithm, lifting scheme

·      Curvelets

presentation1 (pdf)    

For extra reading - presentation1b (pdf) 

 

Lecture 2, 14.01.2013 and 16.01.2013

Image Compression, 4h.

·      Fundamentals: coding redundancy, psycho-visual redundancy, fidelity criteria

·      Source and channel encoding

·      Information theory elements: information measures, coding theorems

·      Loss-lees compression: variable-length coding, bit-plane coding, predictive coding

·      Lossy compression:  predictive coding, transform coding

presentation2 (pdf) 

 

Lecture 3, 21.01.2013 and 23.01.2013 

Image Compression (cont.), 4h.

·      Lossy compression: wavelet coding

·      Compression of the wavelet coefficients: EZT, SPIHT, EBCOT algorithms

·      Standards: JBIG, JPEG, JPEG2000, MPEG

Object Recognition, 1h.

·      Patterns and pattern classes

·      Decision-theoretic recognition methods: matching, optimum statistical classifications, neural networks

·      Structural methods: matching shape numbers, strings and trees

presentation3a (pdf); presentation3b  (pdf)

Lecture 4, 28.01.2013 and 30.02.2013

Image Segmentation, 4h.

·      Detection of discontinuities

·      Edge linking, boundary detection, thresholding

·      Region-based segmentation

·      Motion-based segmentation

presentation4 (pdf) ;

 

Lecture 5, 04.02.2013 and 06.02.2013

Local Approximations in Image Processing, 4h.

·      Local polynomial approximation

·      Anisotropic nonparametric image restoration

·      Image denoising

·      Image deblurring

Material presentation5a (first 40 slides) ;  presentation5b

Further reading :

http://www.cs.tut.fi/~lasip/

http://www.cs.tut.fi/~lasip/papers/LPA-ICI_Book-TICSP_Series_no_19-2003.pdf

http://www.cs.tut.fi/~foi/papers/Foi-Anisotropic_non_parametric_image_processing-2005.pdf

 

Lecture 6, 11.02.2013 and 13.02.2013

Non-local Imaging

Given by Prof. Vladimir Katkovnik, 4h.  

presentation 6 (pdf) (slides 1–16 and 52–227)

 

 

Lecture 7, 25.02.2013

Image quality assesstment

presentation 7 (pdf)

Homework

 

 

 

 

 


Literature

Textbook

[1] R. Gonzalez and R. Woods, "Digital Image Processing, 2nd ed.", Prentice-Hall, 2002.

www.imageprocessingplace.com/

Additional books

[2] John Russ, “The Image Processing Handbook, Fourth Edition”, CRC Press, 2002

[3] Y. Shi, H. Sun, “Image and Video Compression for Multimedia Engineering: Fundamentals, Algorithms, and Standards”, CRC Press, 1999

[4] K. Rao and P. Yip, “The Transform and Data Compression Handbook”, CRC Press, 2001

[5] V.Katkovnik, K.Egiazarian, and J.Astola, “Local Approximations in Signal and Image Processing”, SPIE Press, vol. PM157, 2006, 576 pages


Last modified: 11 December 2013, 14:31 EET