中文摘要：

在计算机图形学与多媒体技术领域，显著性检测具有广泛的应用,已成为许多工作重要的一步.大量计算机图形学与多媒体技术工作（如图像分割、图像标记、视频跟踪）依赖于精确的显著性图.然而，现有的大多数显著性检测算法所得到的结果存在较大缺陷：如边界不明晰、召回率过低等.提出了一种基于矩形波谱分析的显著性检测算法，将图像分块，分别与预先设定好的矩形波构成的模板进行卷积运算，依据所得到的响应，评价某一区域与周围区域的差异性以及在全局中的独特性，赋予其相应的显著性值.通过在不同数据集上的大量实验证明，与现有的大部分显著性检测算法相比,本方法不仅有较高的准确率召回率，且在得到的显著性图中，具有更明晰的边界.

英文摘要：

The saliency detection is an important step in many computer graphic and multi-media technology tasks be- cause of its wide applicability. Computer graphic tasks （such as image segmentation, image labeling and tracking） rely mainly on fine saliency maps. However, most of the existing methods are defective due to their poor ability in generating fine boundary or high recall rate. This paper proposes a saliency detection method. The given image is divided into several regions which convolute with a pre-set rectangle-wave template later. For each region, the final saliency value is determined by the difference between themselves and the regions next to them as well as their uniqueness when they are compared with the whole images according to the corresponding response. Repeated tests on the different data sets prove its high precision-recall rate. Additionally, the boundary in our saliency map is clearer and finer.