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HU Credits:
2
Degree/Cycle:
2nd degree (Master)
Responsible Department:
computer sciences
Semester:
2nd Semester
Teaching Languages:
Hebrew
Campus:
E. Safra
Course/Module Coordinator:
raanan fattal
Coordinator Office Hours:
after class
Teaching Staff:
Prof Raanan Fattal
Course/Module description:
wavelets, sparsity, non-parametric image synthesis and image statistics. The topics will be taught in the context of various image restoration problems, such as denoising, deblurring and super-resolution.
Course/Module aims:
Provide knowledge about natural image modelling with emphasis on application to restoration problems
Learning outcomes - On successful completion of this module, students should be able to:
Provide knowledge about natural image modelling with emphasis on application to restoration problems
Attendance requirements(%):
0
Teaching arrangement and method of instruction:
Lectures
home exercises
exam
Course/Module Content:
wavelets, sparsity, non-parametric image synthesis and image statistics. The topics will be taught in the context of various image restoration problems, such as denoising, deblurring and super-resolution.
Required Reading:
A Wavelet Tour of Signal Processing, Third Edition: The Sparse Way
Mallat
Additional Reading Material:
Course/Module evaluation:
End of year written/oral examination 50 %
Presentation 0 %
Participation in Tutorials 0 %
Project work 0 %
Assignments 50 %
Reports 0 %
Research project 0 %
Quizzes 0 %
Other 0 %
Additional information:
The introduction to image processing course is a prerequisite for this course
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