Unified mean shift segmentation and graph region merging algorithm for infrared ship target segmentation

Unified mean shift segmentation and graph region merging algorithm for infrared ship target segmentation
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红外船舶目标分割统一均值平移分割与图区域合并算法

DOI:
10.1117/1.2823159
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发表时间:
2007-12
影响因子:
1.3
通讯作者:
Tao, Wenbing
Tao, Wenbing
中科院分区:
工程技术4区
文献类型:
--
作者:
Liu, Jin;Jin, Hai;Tao, Wenbing

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我们提出了一种统一的方法,该方法结合了基于均值漂移的图像分割算法和基于SST(最短生成树)-最小最大的图分组方法,以实现适合实时应用的有效红外对象分割性能。该方法利用均值漂移算法对图像进行预处理,形成分割区域,既能去除噪声,又能保持目标的不连续性。分割后的区域可以有效地表示原始图像,通过使用图结构,我们应用SST-minmax方法进行合并过程,以形成最终的分割区域。由于良好的不连续性保持滤波特性,在不损失红外舰船目标信息的前提下,有效地去除了海面背景的杂波干扰,并显著减少了基本图像实体的数量。因此,基于SST-minmax的区域合并算法由于杂波干扰小、区域节点少,能够以较低的计算代价获得较好的分割效果。通过对真实的红外舰船图像序列的大量实验,验证了该方法的优越性。
We propose a unified approach that incorporates the mean shift-based image segmentation algorithm and the SST (shortest spanning tree)-minmax-based graph grouping method to achieve effective IR object segmentation performance amenable for real-time application. It preprocesses an image by using the mean shift algorithm to form segmented regions that can not only remove the noise, but also preserve the desirable discontinuity characteristics of the ship object. The segmented regions can then effectively represent the original image by using the graph structures, and we apply the SST-minmax method to perform merging procedure to form the final segmented regions. Due to the good discontinuity-preserving filtering characteristic, we can effectively remove the clutter disturbance of the sea background without loss of the IR ship object information, and significantly reduce the number of basic image entities. Therefore, the region merging based on SST-minmax can produce excellent segmentation performance at low computational cost due to smaller clutter disturbance and less region nodes. The superiority of the proposed method is examined and demonstrated through a large number of experiments using a real IR ship image sequence.
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发表时间: 1999-09
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