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We present a high-accuracy, low false-alarm rate, and low computational-cost methodology for removing stars and noise and detecting space debris with low signal-to-noise ratio (SNR) in optical image sequences. First, time-index filtering and bright star intensity enhancement are implemented to remove stars and noise effectively. Then, a multistage quasi-hypothesis-testing method is proposed to detect the pieces of space debris with continuous and discontinuous trajectories. For this purpose, a time-index image is defined and generated. Experimental results show that the proposed method can detect space debris effectively without any false alarms. When the SNR is higher than or equal to 1.5, the detection probability can reach 100%, and when the SNR is as low as 1.3, 1.2, and 1, it can still achieve 99%, 97%, and 85% detection probabilities, respectively. Additionally, two large sets of image sequences are tested to show that the proposed method performs stably and effectively.

As a novel multiscale geometric analysis tool, sparse representation has shown many advantages over the conventional image representation methods. However, the standard sparse representation does not take intrinsic structure and its time complexity into consideration. In this paper, a new fusion mechanism for multimodal medical images based on sparse representation and decision map is proposed to deal with these problems simultaneously. Three decision maps are designed including structure information map (SM) and energy information map (EM) as well as structure and energy map (SEM) to make the results reserve more energy and edge information. SM contains the local structure feature captured by the Laplacian of a Gaussian (LOG) and EM contains the energy and energy distribution feature detected by the mean square deviation. The decision map is added to the normal sparse representation based method to improve the speed of the algorithm. Proposed approach also improves the quality of the fused results by enhancing the contrast and reserving more structure and energy information from the source images. The experiment results of 36 groups of CT/MR, MR-T1/MR-T2, and CT/PET images demonstrate that the method based on SR and SEM outperforms five state-of-the-art methods.

The goals of engineering and scientific missions for Chang'E-2 lunar satellite require high detection sensitivity and large imaging dynamic range for the onboard CCD cameras. The TDI CCD image sensor was adopted for the two linear CCD stereo cameras for the first time in the lunar reconnaissance of the world. The design argumentation is described in this paper. The analysis shows that the imagers meet the mission requirements. The satellite was launched on 1 October 2010 at zero window. The cameras obtained images of 7 m resolution on the 100 km orbit for the first time on 24 October 2010, and operated once again on 27 October 2010 to take stereo images of the Sinus Iridum with the resolution better than 1.5 m. On the near-moon-arc of 15 km×100 km elliptical orbit, the images are very clear and rich of grey scales, indicating successful completion of the Chang'E-2 engineering mission. At the present the cameras are acquiring the full lunar surface stereo images with 7 m resolution on the 100 km circular orbit to complete their scientific mission. lunar satellite, Chang'E -2, CCD stereo camera, engineering and scientific target, Sinus Iridum image Citation:Zhao B C, Yang J F, Wen D S, et al. Overall scheme and on-orbit images of Chang'E-2 lunar satellite CCD stereo camera.