The researches on calibration of star sensor rarely involve the exterior parameters and image distortion of the optical
system. In order to get more accurate interior-exterior parameters of the optical system, this paper proposes exact
calibration model and algorithm based on interior-exterior parameters. Basing on analyzing the imaging model of star
sensor, the principle of the star sensor calibration is as follow: firstly, the two-step method is used to get the initial
interior-exterior parameters; then Levenberg-Marquardt optimization algorithm is utilized to get the global optimal
solution. Experiments show that the angular distance of stars can be reduced from 57" to 5.2" after calibration. In
addition, the calibration method can effectively eliminate the coupling of the interior-exterior parameters, achieve higher
measurement accuracy, and significantly improve the recognition rate of the star map.
Subject to limited resolution for targets in many satellite images, low-resolution airplane detection is still difficult and challenging, which plays an important role in remote sensing. In this paper, we propose a new method to detect lowresolution airplanes in satellite images. First, the image is preprocessed by combing the unsharp contrast enhancement (UCE) filtered image and the original image. Second, the Local Edge Distribution (LED), which is susceptible to objects owning clustered edges, e.g., airplane, is calculated to acquire the target candidate regions while restraining large background area. Then, a multi-scale fused gradient feature image is computed to characterize the shapes of targets instead of the original image to overcome the influence from the self-shadow and different coating colors of airplanes. After that, a designed airplane shape filter with a modulated item is used to detect and locate real targets, in which the modulated item can effectively measure the degree of coincidence between the patch region and the airplane shape. Finally, coordinates of target centers are computed in the filtered image. Experimental results demonstrate that the proposed algorithm is effective and robust for detecting low-resolution airplanes in satellite images under various complex backgrounds.
A novel adaptive aircraft detection method based on level set processing and circle-frequency filter is proposed in this paper. First, the SBGFRLS (Selective Binary and Gaussian Filtering Regularized Level Set) method is used twice to find airport region of interest (ROI) and candidate aircraft areas by local segmentation and global segmentation, respectively, so that sizes of those possible target areas can be computed. Then, the circle-frequency (CF) filter method is utilized adaptively to detect target aircrafts in the airport ROI via the mean radius estimated by sizes of those candidate areas obtained before. Experimental results on real remote sensing airport images demonstrate the efficiency and accuracy of the proposed method.