图象分割是自动目标识别系统(ATRS)的关键部分,它是一种基本的图象分析技术,作为图象分析的重要步骤在许多图象应用分析中都是必不可少的,其结果直接影响到其后的信息处理过程.分割算法性能的评估是ATRS离线评估的重要组成之一.根据信息融合与系统工程思想,提出了基于多层次灰色关联度分析的图象分割性能评估模型,该方法综合信息融合、灰色系统和层次分析法等新兴学科精华而成,该方法既可以从整体上进行评估、又可以从某个侧面进行评估.文中给出了该方法同以往方法的实验对比,应用实例显示,它在现有文献的基础上提高了数据的离散性,便于区分不同分割算法的性能,克服了以往方法的奇异性和不灵敏性,它在分割算法的性能评估方面比其他方法更为有效、合理,从而使评判更易进行.

Image segmentation is the key component in the automatic target recognition system (ATRS). It's an important step of image analysis. Its results have critical implications for the information processing stages that follow: The evaluation of a segmentation algorithm makes an important part of the estimation of performance for are as an off-line ATRS; Based on the knowledge of data fusion and systems engineering, a new model of gray multi-hierarchical appraise by combining gray appraise method with the Analytic Hierarchy Process (AHP) and data fusion is proposed in this paper. It is used to evaluate the performance of image segmentation. The performance evaluation can be performed from both global and local aspects. The paper also discussed evaluation models and their experimental comparative results to prove its feasibility and to confirm the advantages of the new model. The application shows that the new model is more efficient and reasonable than other methods.