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:
- Update maps
- Observe urban populations
- Set up radiomobile networks
- Analyze urban areas evolution
One often study urban areas by using the following data:
- Optic satellite images (SPOT, LANDSAT)
- Radar satellite images (ERS, JERS, Radarsat)
- Aerial images
One study urban areas from two point of view in order to:
- Extract a urban mask.
- Distinguish different regions inside the city itself.
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:
- 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.
- 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.
- Segment and regularize through Markovian modelling
- Eliminate false alarms by using an image
- Some results
Last modified: Wed Feb 18 16:59:44 MET 2004