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A convex active contour model driven by local entropy energy with applications to infrared ship target segmentation

机译:由当地熵能驱动的凸起主动轮廓模型,应用于红外船舶目标分割

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摘要

To segment ship target in infrared (IR) images, a convex active contour model based on local image entropy is proposed in this paper. Firstly, local image entropy based on kernel function is obtained; on this basis, the convex energy functional is built using the variational level set method in the convex set. Because of the introduction of entropy, the proposed method can protect the image edge and enhance the ability to deal images with heterogeneity. At the same time, the convex energy functional can get a global minimum and has robustness against initial curve placement. Compared with the state-of-the-art methods, experiment results demonstrate the performance and effectiveness of the proposed method. (C) 2017 Elsevier Ltd. All rights reserved.
机译:为了在红外线(IR)图像中分段船舶目标,本文提出了一种基于局部图像熵的凸有效轮廓模型。 首先,获得了基于内核功能的本地图像熵; 在此基础上,使用凸集中的变分级别设置方法构建凸能功能。 由于引入熵,所提出的方法可以保护图像边缘并增强与异质性交易图像的能力。 同时,凸电能功能可以获得全局最小,并且对初始曲线放置具有鲁棒性。 与最先进的方法相比,实验结果表明了该方法的性能和有效性。 (c)2017 Elsevier Ltd.保留所有权利。

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