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Spatial database updating using active contours for multispectral images: application with Landsat 7

机译:使用活动轮廓绘制多光谱图像的空间数据库更新:Landsat 7的应用

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This paper presents a fully automated approach for area detection and delineation based on multispectral images and features from a topographic database. The vectors residing in the database are refined using active contours (snakes) according to updated information provided by the multispectral images. The conventional methods of defining the external energy guiding the deformation of the snake based on: (1) statistical measures; or (2) gradient-based boundary finding is often corrupted by poor image quality. Here a method to integrate the two approaches is proposed using an estimation of the maximum a posteriori (MAP) segmentation in an effort to form a unified approach that is robust to noise and poor edges. We further propose to improve the accuracy of the resulting boundary location and update of the snake topology. A number of experiments are performed on both synthetic and LANDSAT 7 images to evaluate the approach.
机译:本文提出了一种基于多光谱图像和地形数据库特征的全自动区域检测和轮廓描绘方法。根据多光谱图像提供的更新信息,使用活动轮廓(蛇形图)细化数据库中的矢量。定义引导蛇形变形的外部能量的常规方法基于:(1)统计量度;或(2)基于梯度的边界查找通常会因较差的图像质量而受损。在这里,提出了一种使用最大后验(MAP)分割的估计来整合这两种方法的方法,以努力形成对噪声和不良边缘具有鲁棒性的统一方法。我们进一步建议提高结果边界位置的准确性和蛇形拓扑的更新。在合成图像和LANDSAT 7图像上都进行了许多实验,以评估该方法。

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