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ATR algorithm performance evaluation based on the simulation image and real image

机译:基于模拟图像和真实图像的ATR算法性能评估

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Currently there is no algorithm which can be adapted to all of the imaging conditions. So, it is necessary for us to find a method to evaluate the existing ATR (automatic target recognition) algorithm. We do some researches on ATR algorithm performance evaluation based on test methodology. The basic idea of the algorithm performance evaluation is to establish the relationship model between the image quality characteristics and the algorithm's performance. In this paper, the algorithm performance evaluation's techniques are studied, which include the algorithm performance assessment framework, the universal test image database's creating, and the research of the image quality evaluation model. Firstly, under the guidance of the orthogonal experimental design method, we construct a universal test image database which includes the simulation image and the outfield flight data. And then this paper propose a method to establish the relation model between image quality characteristic and ATR algorithm based on SVM classifier. Finally we use the model to evaluate algorithm's performance. We conduct experiments on the matching algorithm's performance evaluation. The experimental results show that the proposed evaluation framework is efficient and the evaluation model is well.
机译:目前没有算法可以适应所有成像条件。因此,我们必须找到一种评估现有ATR(自动目标识别)算法的方法。我们对基于试验方法的ATR算法性能评估进行了一些研究。算法性能评估的基本思想是建立图像质量特征与算法性能之间的关系模型。本文研究了算法性能评估的技术,包括算法性能评估框架,通用测试图像数据库的创新,以及图像质量评估模型的研究。首先,在正交实验设计方法的指导下,我们构建了一个通用测试图像数据库,包括模拟图像和外场飞行数据。然后本文提出了一种基于SVM分类器的图像质量特性与ATR算法之间的关系模型的方法。最后,我们使用模型来评估算法的性能。我们对匹配算法的绩效评估进行实验。实验结果表明,所提出的评估框架有效,评价模型良好。

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