Representation and Analysis of Visual Images

Brief Description:
A graduate-level lecture course on theory and tools for representing, 
manipulating and analyzing visual images. Topics to include: 
imaging and optics, estimation and representation of position, 
alignment,  displacement and local orientation, multi-scale image 
decompositions, statistical generative models for images, 
low-dimensional and sparse approximation, representation of visual 
structures and patterns. Grades are based on homework, 
which relies on matlab programming.

Prerequisites: linear algebra, linear systems theory (convolution, 
Fourier transforms), probability/statistics. Some matlab programming 
experience.