摘要
A binocular stereo vision positioning method based on the scale-invariant feature trans- form （SIFT） algorithm is proposed. The SIFT algorithm is for extracting distinctive invariant features from images. First, image median filtering is used to eliminate image noise. Then, according to the characteristics of the target satellite, image map is used to extract the middle part of the target satel- lite. At last, the feature match point under the SIFT algorithm is extracted, and the three-dimension- al position and orientation are calculated. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The experimental result shows that the al- gorithm works well and the maximum relative error is within 0. 02 m and 2.5 o
A binocular stereo vision positioning method based on the scale-invariant feature trans- form （SIFT） algorithm is proposed. The SIFT algorithm is for extracting distinctive invariant features from images. First, image median filtering is used to eliminate image noise. Then, according to the characteristics of the target satellite, image map is used to extract the middle part of the target satel- lite. At last, the feature match point under the SIFT algorithm is extracted, and the three-dimension- al position and orientation are calculated. The features are invariant to image scale and rotation, and are shown to provide robust matching across a substantial range of affine distortion, change in 3D viewpoint, addition of noise, and change in illumination. The experimental result shows that the al- gorithm works well and the maximum relative error is within 0. 02 m and 2.5 o
