ANALYSIS OF GROUND SAMPLING DISTANCE OF CONVERGENT IMAGES FOR KEYPOINTS DETECTION FOR CLOSE-RANGE PHOTOGRAMMETRY

Abstract

Keypoint detection for image matching is an important step in close range photogrammetry. It essentially depends upon ground sampling distance (GSD) of an image. For a convergent image, GSD variations on the either side of image axis are not equal. Moreover, GSD also varies according to camera position placed at constant distance from an object. This paper investigates and analyses the GSDs of convergent images for various geometrical configurations of camera positions on a circular arc for a building corner. GSD expressions and rates of GSD change are derived for left and right edges of a convergent image. Both GSD and rate of GSD change are characterized by non-linear mathematical functions of camera FOV, and its position on circular for a given corner. Experiments are conducted to acquire varying number of convergent images on circular arcs of different radius. Keypoints for convergent images are influenced more by rate of GSD change than the GSD. The study determines a critical value of 28 for rate of GSD change. The correct matching of keypoints in two images is limited within FOVs corresponding to the critical value. An example demonstrating the correct keypoint matching for two images is presented.