计算机科学 ›› 2018, Vol. 45 ›› Issue (10): 272-275.doi: 10.11896／j.issn.1002-137X.2018.10.050
陈炳才1,2, 王西宝1, 余超1, 年梅2, 陶鑫1, 潘伟民2, 卢志茂1
CHEN Bing-cai1,2, WANG Xi-bao1, YU Chao1, NIAN Mei2, TAO Xin1, PAN Wei-min2, LU Zhi-mao1
摘要： 针对图像显著性检测问题,提出一种利用被包围状态和马尔可夫模型进行图像显著性检测的方法。首先,利用被包围状态计算显著性物体的大致区域;其次,使用简单线性迭代聚类(SLIC)算法对原始图像进行处理,得到图像的超像素图,并基于超像素图建立图像的图模型;接着,将距离显著性物体大致区域最远的两条边界的超像素作为虚拟背景吸收节点,利用吸收马尔可夫链计算每个超像素的显著性值,检测出初始的显著图S1;再以计算出的显著性物体大致区域中的超像素作为虚拟前景吸收节点,利用吸收马尔可夫链检测出初始的显著性图S2;然后,融合S1和S2得到最终的显著图S;最后,利用引导滤波器对显著图S进行平滑处理得到更优的显著图。在两个数据库上的实验结果表明,提出的算法优于现有大多数算法。
中图分类号:
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