基于图像单元对比度与统计特性的显著性检测

Image Cell Based Saliency Detection via Color Contrast and Distribution

根据视觉注意机制,提出一种基于图像单元对比度与空间统计特性的可靠显著性区域检测方法.通过自适应的图像分割构造图像单元结构,以图像单元为基础,分别利用颜色对比度和空间统计特性两种模型进行显著性区域检测,最后,将两种模型的检测结果通过高斯模型进行结合,得到最终的显著性区域检测的结果.实验表明,该检测方法与现有的方法比较,具有更好的精度和召回率,能明显抑制复杂纹理和噪声,去除复杂背景的影响.

According to biological visual attention mechanism, a salient region detection method is proposed in this paper, which is based on image cell contrast and space statistical characteristics. By constructing image cell structure with an adaptive image segmentation, based on image cell, it makes a salient region detection using both the color contrast model and space statistical characteristics model. In the end, two models~ detection results combine by Gaussian model to get the final salient region detection results. Experiments show that this detection method has a higher precision and recall rate, which can not only resist the complex texture and the noise but also remove the influence of the complex background.