Automatic man-made object recognition in high resolution remote sensing images

With the advent of commercial satellite sensors producing images with resolutions better than 5 m., it is now possible to recognize man-made objects which were not visible at lower resolutions. In this work, an image processing chain for the detection of man-made objects in high resolution remote sensing images are presented. Detection is understood as finding the smallest rectangular area in the image containing the object. These algorithms are based on learning methods and on an example data base which contains 10 classes of objects