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Quantitative performance evaluation on segmentation methods for SAR ship images

机译:SAR舰船图像分割方法的量化性能评估

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Segmentation of target is an important step in forming realistic target models. To assist in classifying the relevant literature, two types of segmentation are identified where each type adds its own additional level of uniqueness. The first type is composed of the simplest forms of image analysis through thresholding, the second is characterized by region based in which the application meets the uncertainty models and optimization effects during segmentation process. The work proposed in this paper explores the strength and weaknesses of the methods and are analyzed for practical purposes. The progress towards the work is validated with SAR image database in which objective and subjective quantitative performance is clearly identified. The comparison is based on the potential performance measures. The methods show special strength in providing designers with an adequate degree of freedom in choosing the proper objects of the SAR image for their application purposes.
机译:目标分割是形成现实目标模型的重要步骤。为了帮助对相关文献进行分类,确定了两种类型的细分,其中每种类型都添加了自己的附加唯一性级别。第一种类型是通过阈值进行图像分析的最简单形式,第二种类型是基于区域的特征,在该区域中,应用程序满足分段过程中的不确定性模型和优化效果。本文提出的工作探讨了该方法的优点和缺点,并针对实际目的进行了分析。通过SAR图像数据库验证了工作进展,该数据库清楚地确定了客观和主观的定量表现。比较是基于潜在的绩效指标。该方法在为设计人员提供足够的自由度以选择SAR图像的合适对象以达到其应用目的方面显示出特殊的优势。

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