AUTOMATIC DEFORMATION INSPECTION METHOD FOR DIGITAL AERIAL IMAGERY BASED ON STATISTICAL CHARACTERISTICS
Keywords: Digital Aerial Imagery, Imagery Deformation, IMU Data Accuracy, Automatic Deformation Inspection, Statistical Characteristics, Cubic Spline Curve
Abstract. The geometric distortion of the push-broom digital aerial imagery can be rectified according to the data of the inertial measurement unit (IMU). The low precision of IMU data will cause the undulant wavelike twist deformations of the push-broom digital aerial images after geometric rectification, directly influencing the authenticity and liability of images and their practical applications. At present, the image deformation diagnosis mainly depends on the subjective judgement of human being, which costs much time and manpower. In the paper, an automatic deformation inspection method based on statistical characteristics for digital aerial imagery is proposed to inspect the distortion caused by the low IMU data accuracy. For the undulant wavelike deformation image has the characteristic of pixel displacement in the regularly same direction, there will be a lot of wave curves in the same direction appeared in the image after geometric correction. Therefore, in the method, the positions of the wave curves in the image will be located by the extreme points of curvature of the contour lines, and then the wavelike deformations can be judged automatically through the distribution statistics of the open directions of the wave curves. The specific implement method can be described as follows: firstly, the edges of the image are detected with Canny edge detector and the vector contour lines are obtained by tracing the edges to get contour lines and fitting them with the cubic spline curve method. Then, the extreme points of curvature of the contour lines are calculated, and some of these points are determined to be the vertexes of the wave curves by judging the positional relations between each extreme point and the points around it, thus constituting a vertex set. Afterwards, the perpendicular directions of the tangent of the vertexes are used as the directions of the wave curves, and then the direction histograms of all the wave curves in the image are obtained by statistical analysis. Finally, the existence of the deformation phenomenon in the image due to the low precision of IMU data is able to be judged based on whether the directions of the wave curves are centralized in a certain direction or not. Experimental results showed that the automatic deformation inspection method presented in this paper can detect the deformation of the digital aerial images effectively caused by low accuracy of IMU data with 95% accuracy.