Edward M. Mikhail 
MULTI-SOURCE FEATURE EXTRACTION AND VISUALIZATION 
IN URBAN ENVIRONMENTS 
Edward M. Mikhail 
Head, Geomatics Engineering 
1284 Civil Engineering Building 
Purdue University 
West Lafayette, IN 47907-1284, USA 
mikhail @ecn.purdue.edu 
KEY WORDS: Sensor Model, Invariance, Hyperspectral, Building Extraction, Road Grid, Visualization 
ABSTRACT 
Basic research is being performed by a team composed of specialists in photogrammetry, spatial image analysis, remote 
sensing, computer vision, and visualization, for the purpose of efficiently extracting urban features from multi-image 
sources and construction and visualization of the resulting database. The team members work cooperatively such that 
the effort is an integrated research. Topics discussed include: sensor modeling for data registration, photogrammetric 
invariance, DEM supported classification of hyperspectral imagery, DEM and thematic data supported building 
extraction, DEM supported road-grid extraction, and visualization in support of photogrammetry and exploitation 
research. 
1 INTRODUCTION 
Extraction of information from imagery has been the domain of photogrammetry, remote sensing, and image 
understanding/computer vision for many years. To be sure, the types of imagery used and the theories and techniques 
applied have varied somewhat from one of these three disciplines to another. Nevertheless, the primary objective of all 
is to obtain correctly labeled features which are geometrically and positionally accurate enough to be useful for a 
variety of applications. The practice in the past has been for researchers and practitioners in each of these three areas to 
work essentially independently from others. Of course, each area was aware of the activities of the others, and 
attempted to adapt and use methodologies developed by the others to the extent possible by their understanding of such 
methodologies. The increased prevalence of imagery in digital form, and the introduction of new sources of data, 
brings to focus the inadequacy of such independent pursuit of a similar goal. It has become quite apparent that 
combined integrated team research by experts in these fields is likely to yield significantly more than what can be 
expected from the sum of the individual efforts. Nowhere can this be more apparent than in the extraction and 
visualization of labeled spatial features in urban environments. This task has been, and continues to be, the most 
demanding in time and effort. In order to meet this challenge, and to put in place a team to address this problem in an 
integrated fashion, the US Army Research Office, under the Multidisciplinary University Research Initiative, MURI, 
awarded a 5-year project to Purdue University as the lead institution. The MURI team members and their speciality 
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