Introduction to Variational Models in Image Processing
Ginmo Chung, Yasunori Kimura · EPrints - Department of Mathematics, Hokkaido University · 2008
Course description: This lecture note is a short introduction to problems arising in image processing and computer vision such as image restoration and image segmentation. They have applications in the areas such as medical imaging, computer animation, just to name a few. Topics include the direct method of the calculus of variations, anisotropic diffusions, functions of bounded variation(BV ), numerical methods for solving PDEs, cartoon-texture image decomposition f = u+ v, Yves Meyer’s G-norm, the characterization of the ROF, level set method, geometric energy functionals and geodesic active contours, and Mumford-Shah image segmentation problem.