Front-End Vision and Multi-Scale Image Analysis

Image analysis is the extraction of useful information from images. In this course we give a modern mathematical (and physics based) approach to multi-scale image analysis as a branch of computer vision. We give an intuitive introduction to multi-scale image analysis, trying to keep the analogy with stages in the human visual system as close as possible. The human visual system also widely exploits a diversity of multi-scale filters in its processing layers.

Among the topics covered are: filters to sample and analyze images, the use of filters in detecting edges and corners in images, multi-scale analysis of 2D and 3D shape and motion from image sequences, depth from stereo, orientation analysis, and the use of contemporary, well-understood mathematical tools in this field such as differential geometry and tensor analysis.

The majority of the examples discussed are from 2D, 3D and 4D (3D-time) medical imaging. We devote some time to the efficient numerical implementation of the different techniques. Hands-on experience is acquired in a computer lab, where experiments in Mathematica 8 illustrate the theory and applications in practice.