Johns Hopkins University 4 credits Applied Mathematics & Statistics
This course gives an overview of various mathematical methods related to several problems encountered in image processing and analysis, and presents numerical schemes to address them. It will focus on problems like image denoising and deblurring, contrast enhancement, segmentation and registration. The different mathematical concepts shall be introduced during the course; they include in particular functional spaces such as Sobolev and BV, Fourier and wavelet transforms, as well as some notions from convex optimization and numerical analysis. Most of such methods will be illustrated with algorithms and simulations on discrete images, using MATLAB. Prerequisites : linear algebra, multivariate calculus, basic programming in MATLAB. Recommended Course Background: A solid foundation Multivariable Calculus, Linear Algebra, and Probability. Real Analysis may help too, but it is not necessary. Prerequisite(s): Students may receive credit for EN.550.493/EN.553.493 or EN.553.693, but not both.
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