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14 December 2015 A pseudo oversampling-based C3PC algorithm for close space objects detection and localization
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Proceedings Volume 9812, MIPPR 2015: Automatic Target Recognition and Navigation; 981215 (2015) https://doi.org/10.1117/12.2210934
Event: Ninth International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2015), 2015, Enshi, China
Abstract
Target cluster brings about a light-spot which consists of several neighborhood pixels in image, therefore it is difficult to distinguish between the targets or locate them with sub-pixel accuracy. In this paper, a pseudo oversampling-based C3PC (Covariance Constrained Constructive Particle Clustering) method is proposed to solve the closely space objects problem. As a classical detection and location method, C3PC algorithm, presents a particle clustering decomposition technique. However, the particle distribution according to the pixel gray value yields pixel level accuracy, which will lead to location error. Thus, by using a particle distribution at sub-pixel level, substantially better position accuracy can be obtained. According the characteristic of oversampling, an improved interpolation algorithm which simulating the oversampling techniques of sensor is brought forward. Simulation experiment results show that the positioning accuracy of CSOs in our algorithm is higher than that of C3PC algorithm.
© (2015) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jing Hu, Fan Dong, and Shinie Cai "A pseudo oversampling-based C3PC algorithm for close space objects detection and localization", Proc. SPIE 9812, MIPPR 2015: Automatic Target Recognition and Navigation, 981215 (14 December 2015); https://doi.org/10.1117/12.2210934
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