Coursebooks

Image processing II

MICRO-512

Lecturer(s) :

Liebling Michael Stefan Daniel
Sage Daniel
Unser Michaël
Van De Ville Dimitri Nestor Alice

Language:

English

Summary

Study of advanced image processing; mathematical imaging. Development of image-processing software and prototyping in JAVA; application to real-world examples in industrial vision and biomedical imaging.

Content

• Review of fundamental notions. Multi-dimensional Fourier transform. Convolution. z-transform. Digital filters.
  
• Continuous representation of discrete data. Splines. Interpolation. Geometric transformations. Multi-scale decomposition (pyramids and wavelets).
  
• Image transforms. Karhunen-Loève transform (KLT). Discrete cosine transform (DCT). JPEG coding. Image pyramids. Wavelet decomposition.
  
• Reconstruction from projections. X-ray scanners. Radon transform. Central slice theorem. Filtered backprojection. Iterative methods.
  
• Deconvolution. Inverse and Wiener filtering. Matrix formulations. Iterative techniques (ART).
  
• Statistical pattern classification. Decision making. Bayesian classification. Parameter estimation. Supervised learning. Clustering.
  
• Image analysis. Pixel classification. Contour extraction and representation. Shape. Texture. Snakes and active contours.

   

Learning Prerequisites

Required courses

Image Processing I

Recommended courses

Signals and Systems I & II, linear algebra, analysis

Important concepts to start the course

Basic image processing and related analytical tools (Fourier transform, z-tranform, etc.)

Learning Outcomes

By the end of the course, the student must be able to:

• Construct interpolation models and continuous-discrete representations
• Analyze image transforms
• Design image-reconstruction algorithms
• Formalize multiresolution representations using wavelets
• Design deconvolution algorithms
• Perform image analysis and feature extraction
• Design image-processing software (plugins)
• Synthesize steerable filters

Transversal skills

• Plan and carry out activities in a way which makes optimal use of available time and other resources.
• Manage priorities.
• Access and evaluate appropriate sources of information.
• Use both general and domain specific IT resources and tools