** **

** Advanced Image Processing **

Spring 2009

**Instructors:**- Sviatoslav Voloshynovskiy (Office 215, Office hours: Tuesday 11.00-12.00 or according to appointment by email)
- Stephane Marchand-Maillet (Office 212, Office hours: Tuesday 11.00-12.00 or according to appointment by email)
**Teaching Assistant:**- Taras Holotyak (Office 226)
**Address:**- Battelle Building A,
- 7, route de Drize,
- 1227 Carouge
- CUI, University of Geneva

**Course Outline**

**Recall of Linear Algebra. Multidimensional Signal Processing**( ~1.5 lectures)**Introduction. Human Visual System**( ~0.5 lecture)**Image Representation : pyramids and wavelets**( ~1 lecture)**Random signals**( ~1 lecture)**Image Modeling**( ~3 lectures)**Image Sensor Models**( ~0.5 lecture)**Noise Models**( ~0.5 lecture)**Image Denoising**( ~1 lecture)**Image Restoration**( ~1 lecture)**Image Compression**( ~1 lecture)**Video Modeling and Compression**( ~1 lecture)**Digital Data Hiding**( ~2 lectures)**Supplementary Materials:**- A.K.Jain, Fundamentals of Digital Image Processing, Prentice-Hall, 1989.
- A.M.Tekalp, Digital Video Processing, Prentice-Hall, 1995.
- A.Bovik, Handbook of Image Video Processing, Academic Press, 2000.
- H.Stark and J.W.Woods, Probability, Random Processes, and Estimation Theory for Engineers, Prentice-Hall, 1994.
- A.M.Yaglom, Correlation Theory of Stationary and Related Random Functions I: Basic Results, Springer-Verlag, 1987.
- L.Breiman, Probability, SIAM, 1992.
- H.V.Poor, An Introduction to Signal Detection and Estimation, 2nd Ed., Springer-Verlag, 1994.
- A.Gersho and R.M.Gray, Vector Quantization and Signal Compression, Kluwer, 1992.
- M.Vetterli and J.Kovacevic, Wavelets and Subband Coding, Prentice-Hall, 1995.
**Useful Links:**- Rice University Signal Processing Information Base: http://spib.rice.edu/spib.html
- Signal processing links of Stanford: http://www.stanford.edu/group/compression/
- C.Bouman's ICIP'95 Tutorial on Markov Random Fields
- Error correction codes: www.eccpage.com
- Image processing software: http://www.efg2.com/Lab/Library/ImageProcessing/SoftwarePackages.htm
- Watermarking World: http://www.watermarkingworld.org/

Vector and matrix image presentations, discrete and continuous Fourier transforms.

Modulation transfer function, visual masking, noise visibility, color vision;

Distortion measures.

Stochastic presentation of images;

Stationary continuous- and discrete-space models, including AR, MRF, stationary Generalized Gaussian;

Nonstationary models: non-stationary Gaussian, HMM;

Transform-based models (DFT, DCT, wavelet);

Edge and texture models;

Doubly stochastic processes;

Relationships between models.

Optical, radar and medical coherent/noncoherent imaging applications:

(aperture difraction constrains, defocusing, motion blur, atmospheric turbulence, sparse imaging apertures);

Photographic film;

Electronic imaging;

CCD imaging applications;

Smart sensors.

Additive noise: Poisson, Gaussian and Laplacian models;

Multiplecative noise: speckle model.

Maximum-likelihood estimation;

Bayesian estimators;

Models selection (MDL principle);

Transform-based denoising: adaptive Wiener filtering, soft-shrinkage and hard-thresholding.

Statistical ill-posed problems;

Deterministic regularization: Tikhonov, edge-preserving and adaptive regularizations;

Transform-based restoration;

Blind deconvolution.

Basics of source coding theory (lossless and lossy);

Vector quantization, codebook design;

Transform and subband coding;

Relationship between compression and denoising.

3-D and 2-D Motion models;

Block matching (simple, hierarchical, and overlapped), optical flow;

Transform-based models;

Motion-compensated prediction models;

Transform and motion-based compression techniques;

Bidirectional prediction.

Steganography (secure communications);

Digital watermarking: fundamentals, channel coding, masking, robustness against geometrical transforms and applications

(robust watermarking, tamper proofing and self-recovering, document authentication, access control, indexing).