Saliency detection with color contrast based on boundary information and neighbors
Saliency detection with color contrast based on boundary information and neighbors
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DOI：
10.1007/s00371-014-0930-9
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发表时间：
2015-03
期刊：
影响因子：
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通讯作者：
Min Xu;Hanling Zhang
中科院分区：
文献类型：
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作者：
Min Xu;Hanling Zhang
物体级显著性检测在许多计算机视觉任务中具有重要意义。提出了一种基于颜色对比度和图像边界的显著性检测模型。图像的显著性被定义为图像元素（区域）和图像边界元素（区域）之间的对比度。我们考虑的显着性在两个阶段的程序，而不是在一个阶段。首先，根据显著性的定义，分别考虑图像的四个边界，得到一个组合的粗糙显著图。在此基础上，提出了一种新的基于粗糙显著图的能量函数，该能量函数以粗糙显著图为输入，生成最终的全分辨率显著图。在两个公开数据集上的实验结果表明，该模型的性能优于现有的方法。
Object-level saliency detection is significant in many computer vision tasks. In this paper, we propose a novel saliency detection model based on color contrast and image boundaries. The saliency of an image is defined as the contrast between the image elements (regions) and image boundaries elements (regions). We consider the saliency in two-stage procedure rather than in one stage. First of all, according to the definition of saliency, we take four boundaries of image into consideration respectively to obtain a combination coarse saliency map. Furthermore, a new energy function based on the coarse saliency map is proposed, which takes the coarse saliency map as input to yield the final full resolution saliency map. Experimental results on two public datasets demonstrate that the proposed model performs better than the state-of-the-art methods.