Runway Detecting From Remote Senesing Image

Edge detection is important in image procession. This thesis made a summary and analysis of edge detecting algorithm and edge detector. Canny has proposed three criterias to describe the performance of different filters: good detection, good localization and low-responses, are introduced in this thesis. Based on analyzing the structure feature of runway, a fast algorithm to detecting edge with embedded confidence is presented in this thesis. The experimental results show that the algorithm is good.Straight lines are very important intermediate level symbol in image analysis. There are drawbacks in the existing algorithms. Although there are many mature algorithms in edge detection, few approaches can extract straight lines from edge images. A fast algorithm to extracting straight lines from edge images is proposed in this thesis. Firstly the structure characteristic is analyzed, and then the conception of linear primitive is given, finally the rules of linear primitive and straight lines connecting are proposed. The experimental results show that the new algorithm is speedy, meanwhile, noise is suppressed well. The perfect performance of the new algorithm allows it to be used in wide application.A fast algorithm to detecting runway from high resolution remote sensing images is presented in this thesis. Edge detection with embedded confidence and straight-line-based primitive extraction are introduced, the former increases the reliability of the detecting results, the latter expedite the detecting speed. The experimental results show that the algorithm is speedy and robust.