Population density estimation using textons

In this paper we propose an efficient method for population density estimation using textons and k nearest neighbor classifier (k-NN). Leung Malik (LM) filter bank is used for texture extraction (textons) from Google Earth Satellite Images and classification into high, medium, low population density and non-populated areas. We have tested the proposed method for 5 different images of cities of Pakistan at high resolution. Comparison of our results with those obtained using Grey Level Co-occurrence Matrix (GLCM) are also presented, indicating the effectiveness of the proposed method.