In this paper, a road detection algorithm from the low illumination remote sensing images is proposed. First, the top-hat transform is used to enhance the edge information in low illumination images. Next, a road detection method based on parallel lines is proposed to detect the parallel characteristics of the two edges of the road. The experiment results show that the proposed algorithm can detect the road information effectively and precisely.
In this paper, we propose an automatic method for high precision measurement and 3D reconstruction of non-cooperative spacecraft based on binocular vision. The Zhengyou Zhang’s calibration method was implemented to calibrate the camera’s internal and external parameters; the 8-point algorithm was adopted to compute the fundamental and essential matrix between the cameras; we got the relative position of binocular camera by the method of the SVD of essential matrix; a stereo matching algorithm depending on the Semi-Global Matching was adopted for disparity map. Subsequently, the cloud information of world points was calculated through least square method. In our experiment, a complex outdoor scene was used. We made a satellite model which has the same size of the real one. To get the accurate position and angle of the spacecraft, the ellipse marks on the spacecraft was exacted effectively under three constraints. The experimental results show that the spacecraft model can be reconstructed accurately by our method. The method contributes the error rate of 1% for the test length and 3% for the test angle in 1 meter.