This project deals with the automatic detection of roads in high resolution satellite images. Suggested approach comprises of preprocessing the satellite image via a series of wavelet based filter banks based on frequency response of the corresponding FIR filter. Here we use a two different wavelet bases in order to filter and de noise the satellite image. The resulting two images are fused together in to a single image of same size as the original satellite image using  Karhounen–Louve transform (KLT) transform which is based on Principal component analysis (PCA). Then a fuzzy inference algorithm is used to detect roads based on statistical information and on geometry which classifies each pixel as road or non–road with regard to fuzzy inference rules yielding in a binary image. This output is then fed as input to the geographical information system (GIS) for the purpose that are in need.