Name: Tibor Lukic
Affiliation: Chair for Mathematics Faculty of Technical Sciences, University of Novi Sad, Novi Sad, Serbia
Primary research interest: Applied Mathematics, Optimaztion, Image Processing
Title of the lecture: Linear and Nonlinear Mathematical Models in Image Processing
Keywords: Affine transformation, Homography, Computer Vision, Total Variation, Tomography
Summary: The presentation will begin with an introduction to linear transformations in image processing. The discussion will focus on affine, projective, and homography transformations. Camera pose estimation is a central problem in computer vision; therefore, we will clarify the projective camera model, including the mathematics involved in transforming a world point into an image point. Nonlinear transformations, such as total variation, play a crucial role in many image processing models—for example, denoising, deblurring, and tomographic image reconstruction. Incorporating a priori information about the original object into these models is known as regularization. Many regularization techniques are based on nonlinear transformations, which will be discussed in the presentation.