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VLSI implementation of star detection and centroid calculation algorithms for star tracking applications

机译:用于恒星跟踪应用的恒星检测和质心计算算法的VLSI实现

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Nowadays, hardware implementation of image and video processing algorithms on application specific integrated circuit (ASIC) has become a viable target in many applications. Star tracking algorithm is commonly used in space missions to recover the attitude of the satellite or spaceship. The algorithm matches stars of the satellite camera with the stars in a catalog to calculate the camera orientation (attitude). The number of stars in the catalog has the major impact on the accuracy of the star tracking algorithm. However, the higher number of stars in the catalog increases the computation burden and decreases the update rate of the algorithm. Hardware implementation of the star tracking algorithm using parallel and pipelined architecture is a proper solution to ensure higher accuracy as well as higher update rate. Noise filtering and also the detection of stars and their centroids in the camera image are the main stages in most of the star tracking algorithms. In this paper, we propose a new hardware architecture for star detection and centroid calculation in star tracking applications. The method contains several stages, including noise smoothing with fast Gaussian and median filters, connected component labeling, and centroid calculation. We introduce a new and fast algorithm for star labeling and centroid calculation that needs only one scan of the input image.
机译:如今,在专用集成电路(ASIC)上图像和视频处理算法的硬件实现已成为许多应用中的可行目标。恒星跟踪算法通常用于太空任务,以恢复卫星或飞船的姿态。该算法将卫星摄像机的星星与目录中的星星进行匹配,以计算摄像机的方向(姿态)。目录中的恒星数量对恒星跟踪算法的准确性有重大影响。但是,目录中较多的恒星会增加计算负担,并降低算法的更新率。使用并行和流水线架构的星形跟踪算法的硬件实现是确保更高准确性和更高更新率的正确解决方案。噪声过滤以及照相机图像中恒星及其质心的检测是大多数恒星跟踪算法的主要阶段。在本文中,我们提出了一种新的硬件架构,用于恒星跟踪应用中的恒星检测和质心计算。该方法包括几个阶段,包括使用快速高斯和中值滤波器进行噪声平滑,连接的组件标记以及质心计算。我们引入了一种新的快速算法,用于星标和质心计算,只需要扫描输入图像一次即可。

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