  The development and application of various remote sensing platforms result in
the production of huge amounts of satellite image data. Therefore, there is an
increasing need for effective querying and browsing in these image databases.
In order to take advantage and make good use of satellite images data, we must
be able to extract meaningful information from the imagery. Hence we proposed a
new algorithm for SAR image segmentation. In this paper we propose segmentation
using vector quantization technique on entropy image. Initially, we obtain
entropy image and in second step we use Kekre's Fast Codebook Generation (KFCG)
algorithm for segmentation of the entropy image. Thereafter, a codebook of size
128 was generated for the Entropy image. These code vectors were further
clustered in 8 clusters using same KFCG algorithm and converted into 8 images.
These 8 images were displayed as a result. This approach does not lead to over
segmentation or under segmentation. We compared these results with well known
Gray Level Co-occurrence Matrix. The proposed algorithm gives better
segmentation with less complexity.
