In this course, you will be introduced to more advanced image analysis methods enabling to enrich your geo-information problem solving abilities. Image processing methods treated in previous courses, such as linear filters, feature based DTM production and conventional hard pixel based classification, face limitations making them insufficient for reliable geo-information extraction in automatic settings. Non-linear filters will be introduced for reduction of noise while preserving the boundaries. In addition, interest operators will be introduced to detect stable structures in images that are invariant to scale and rotation transformation. Various methods for dealing with objects in images will be studied: mathematical morphology and segmentation. Fuzzy and sub-pixel classification will be introduced to deal with uncertainty and to increase the information content extracted from the imagery. For multisource classification decision trees will be introduced. To automatically detect corresponding image positions, the image matching techniques will be introduced. In particular, area-based matching and feature-based matching will be investigated in this course.