25-10-2012, 11:54 AM
Use of Machine Vision Techniques to Detect Human Settlements in Satellite Images
ABSTRACT
The automated production of maps of human settlement from recent satellite images is essential to studies of urbanization,
population movement, and the like. The spectral and spatial resolution of such imagery is often high enough to successfully
apply computer vision techniques. However, vast amounts of data have to be processed quickly. In this paper, we propose an
approach that processes the data in several different stages. At each stage, using features appropriate to that stage, we identify
the portion of the data likely to contain information relevant to the identification of human settlements. This data is used as
input to the next stage of processing. Since the size of the data has reduced, we can now use more complex features in this
next stage. These features can be more representative of human settlements, and also more time consuming to extract from
the image data. Such a hierarchical approach enables us to process large amounts of data in a reasonable time, while
maintaining the accuracy of human settlement identification. We illustrate our multi-stage approach using IKONOS 4-band
and panchromatic images, and compare it with the straight-forward processing of the entire image.