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Line matching using a disparity map in rectified image space for stereo aerial images

ABSTRACT This study proposes a novel line-matching method that uses a disparity map in rectified image space for stereo aerial images. Two original images are first rectified to images in the rectified image space by a rectifying projection. The disparity map is then built by dense matching technology in the rectified image space. For an unmatched line segment, the surrounding pixels on the disparity map can be triangulated into 3D points, which can be used to compute rectified planar homography and obtain a predicted line segment. The candidate matches are determined by calculating line similarity as measured by position and orientation shifts with respect to the predicted line segment. Three pairs of calibrated aerial images were used to demonstrate the efficiency and validate the proposed method. Compared with another line-matching method using sparse image points, the number of matches, accuracy and completeness are improved in the proposed method.