Building extraction from very high resolution multispectral images using NDVI based segmentation and morphological operators

In this paper, we have proposed an approach for building extraction from very high resolution (VHR) multispectral images using NDVI (Normalized Difference Vegetation Index) based segmentation and morphological operations. This approach uses both spatial and spectral properties of an image scene for building detection. Spectral properties are related to NDVI based segmentation and spatial properties are related to the morphological operations. Normally an image scene consists of natural region (vegetation and soil) and manmade regions (buildings and roads). Use of NDVI (spectral properties) eliminates the chance of shadow being a building region and other similar regions that are not road like soil, vegetation etc because shadow is a spatial property and NDVI is based on spectral property irrespective of brightness in the image. By using NDVI we can eliminate the natural regions from the manmade regions because NDVI values of these two regions differ a lot, so using NDVI as a threshold we can segment image into two parts one is natural and other is our desired parts that consists of manmade regions (buildings and roads). After segmentation here comes the use of spatial property, use of morphological operation to separate the roads from building regions on the basis of their spatial property that roads have elongated and larger area than buildings and mostly building has the rectangular rooftops. This approach provides very satisfactory results with very less overhead and time.