What is the Problem and What are the Applications?

One can analyse urban areas through remote sensing. This analysis is very useful in many fields:

One often study urban areas by using the following data:
  1. Optic satellite images (SPOT, LANDSAT)
  2. Radar satellite images (ERS, JERS, Radarsat)
  3. Aerial images

One study urban areas from two point of view in order to:

Our Objective

Firstly we aim at precisely defining a urban mask from high resolution satellite images (SPOT5). You cannot extract urban areas from satellite images through only grey level information. Hence some approaches use mathematical morphology. Others approaches use classical texture parameters (coocurrence matrix, vegetation index...). In this work we model the image by a Markov randon field.

The steps are the following:

  1. Analyze the texture of urban areas through a Markovian modelling. We defined a new textural parameter derived from a Markovian Gaussian model. This new parameter takes into account the variance of the image in eight directions.
  2. Classify the image of parameter by a modified fuzzy Cmeans algorithm. This algorithm include an entropy term. The number of classes does not need to be known a priori.
  3. Segment and regularize through Markovian modelling
  4. Eliminate false alarms by using an image of markers.
  5. Some results

    Last modified: Wed Feb 18 16:59:44 MET 2004