A novel point pattern matching algorithm based on point feature is proposed. In the paper, we construct the point's feature map, according to the point set's distribution and points' position. Then the log-polar coordinate transformation is applied to the feature map, and the moment invariants method is used to describe the transformed feature map and it's written by the form of vectors. Thus, the curse matching results is acquired by comparing the feature vectors. After these, an iterative method,the relaxation labeling method, is introduced for the final matching result. There are two contributions made in this paper. Firstly, we construct a log-polar coordinate transformation based point feature(L-PTM), which can stand affine transformation.Secondly, a new point pattern matching algorithm is proposed, which is combined L-PTM with the relaxation labeling. The method is insensitive to outliers and noises. Experiments demonstrate the validity and robustness of the algorithm.
Range gating is a kind of effective method which can eliminate backscattered light and increase the SNR of the
laser range gated (LRG) imaging system. In the paper, we describe a computer model that was developed to simulate the
imaging data of the LRG system. It is used to help design LRG system, and also acquire LRG imaging data used for
further research on surveillance, city topography, combat identification, and other applications. The experiments are
made in the condition of varied pulse energy, range gate width, atmospheric transmition, then the simulation result is
analyzed and the related conclusion is obtained. It demonstrates that the simulating image data is suit for further study on