Deep-space object detection based on non-recursion iterative projection

Traditional method could not detect all objects, when the deep-space image is low SNR and full of distortion. To tackle this problem, a fast and real-time deep-space object detection approach was proposed, which was based upon modified iterative projection and non-recursion programming method. In this algorithm, a coarse-to-fine detection process was used. Firstly, the number of projection was determined adaptively in accordance with the image unique properties to detect all objects. Then the trajectory matching was undergone by neighborhood decision approach to achieve accurate objects detection. To implement the algorithm in real time, a non-recursion program method was used to optimize the structure of the hardware. So, the proposed algorithm was easy to implement by FPGA. Experimental results on SOPC hardware platforms show that it can perform real-time detection accurately for the deep-space objects, and it plays a decisive role for the success of the experiment on suspension.