摘要

针对现有显著性检测方法存在背景抑制效果差和前景分辨率低的问题,提出一种基于背景抑制和前景更新的显著性检测方法。首先利用MR(manifold ranking)算法计算背景先验图,通过超像素分割算法提取的边缘超像素来构建背景模板,计算出稀疏重构图,点乘运算获得高质量的背景抑制图;同时利用高斯混合模型计算颜色先验图,通过CA(Cellular Automata)模型计算多尺度下的颜色优化图,点乘运算获得高精度的前景更新图;最后在贝叶斯框架下融合背景抑制图和前景更新图获得满足人眼要求的最终显著图。在2个公开数据集上的实验结果表明,本文算法能够获得背景抑制效果明显、前景分辨率高的显著图,并且其准确率、F-measure、平均绝对误差(MAE)等指标均优于其他8种对比算法。

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