Image processing II
MICRO-512 / 3 credits
Teacher(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 Jupyter Notebooks; application to real-world examples in industrial vision and biomedical imaging.
Content
- Directional image analysis. Mathematical foundations. Structure tensor. Steerable 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 in the continuum. Wiener filter. Radon transform. Fourier slice theorem. Filtered backprojection.
- Computational imaging. Imaging as an inverse problem. Iterative reconstruction methods. Elements of convex analysis. Regularization & sparsity constraints.
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.)
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
- 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
- Construct interpolation models and continuous-discrete representations
- Analyze image transforms
- Design image-reconstruction algorithms
- Formalize multiresolution representations using wavelets
- Perform image analysis and feature extraction
- Design image-processing software
- Design image reconstruction algorithms
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
Assessment methods
The objectives of the course will be assessed as follows:
- 70% final exam
- 30% IP labs
In the programs
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
- Exam form: Written (summer session)
- Subject examined: Image processing II
- Lecture: 3 Hour(s) per week x 14 weeks
- Type: optional
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