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USE OF STATISTICAL DISTRIBUTION FOR SEGMENTATION OF SAR IMAGES OF OCEANIC AREAS

机译：使用统计分布进行海洋区域SAR图像分割

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摘要

In this work the use of statistical techniques will be approached for segmentation of SAR images, with the purpose of ship detection, being used RADARSAT images of the Brazilian coast. As described in Rocha et al (2001) and Rocha and Stech (2003), a specific software for ship detection was developed where, based on Eldhuset (1996), Vachon et al (1997), Oliver and Quegan (1998), Zaart et al (1999), Ferreira et al (2000) and Macedo et al (2001), some routines were implemented for the use of several statistical distributions for the segmentation of the images, as, for example, the Weibull, Gama, and K distributions. Initially, the shape and scale factors were dear in function of the statistical characteristics of each image, as average, variance and standard deviation. However due to the variability of these characteristics in agreement with each image, they were established values patterns for these factors, that allowed a desirable adaptation of the curve of the distribution to the curve of the histogram of the image. These routines were, then, tested for this group of images and its results were analyzed. The results were analyzed individually, through a comparison among them and, also, using a RGB composition among them.
机译：在这项工作中，将使用统计技术的使用，用于SAR图像的分割，目的是船舶检测，被巴西海岸的雷达图像使用。如Rocha等（2001）和Rocha and Stech（2003）中所述，开发了一种特定的船舶检测软件，基于Eldhuset（1996），Vachon等人（1997），Oliver和Quegan（1998），Zaart et al（1999），Ferreira等（2000）和Macedo等人（2001），一些例程是为使用几种统计分布而用于分割图像，例如，威布尔，GAMA和K分布。最初，形状和比例因子是亲爱的，符合每个图像的统计特征的功能，平均，方差和标准偏差。然而，由于与每个图像一致的这些特征的可变性，它们是为这些因素的成立的值模式，其允许将分布曲线的理想调整到图像的直方图的曲线。然后，这些惯例是针对该组图像进行测试，并分析其结果。通过在它们中的比较中，单独分析结果，并且还使用其中的RGB组合物进行分别进行分析。

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