基于中低层结合的图像感兴趣区域标注  

Region of Interest Marked by Low and Middle Levels

作　　者：周洁 王士同 Zhou Jie;Wang Shitong(School of Digital Media,Jiangnan University,Wuxi,214122,China)

机构地区：[1]江南大学数宇媒体学院,无锡214122

出　　处：《数据采集与处理》2018年第2期379-388,共10页Journal of Data Acquisition and Processing

基　　金：国家自然科学基金(61170122)资助项目。

摘　　要：图像感兴趣区域标注是近年来图像处理领域的重要研究课题之一。利用中低层次信息相结合的方式确保中低层信息相互补充,可以得到可靠结果。中层次显著图由改进的Harris角点形成的凸包区域与GBR超像素聚类结果相结合得到,低层次信息由不同权重的高斯差分滤波器对图像进行处理得到。最后通过加权融合两个层次显著图得到最终结果。本文利用微软亚洲研究院公开数据库对实验结果进行验证,并选取其他前沿方法进行对比,从主观和客观角度对实验结果进行判断,本文方法结果较好,可准确定位显著度区域并高亮表示,同时可有效消除背景噪声。Image marking of the region of interest is an important research topic in image processing in recent years.The combination of low and middle levels can ensure the result has both of their information.First,we get the middle-level coarse saliency map by using the boosting Harris to make a convex hall and superpixels clustered by GBR.And then we weight different Gaussian filters to get the low-level saliency map.The final saliency map is combinated by middle-level saliency map and low-level saliency map.Experiments on the public databases coming from Microsoft Research Asia show that the proposed algorithm performs better than state-of-art algorithms not only on subjective evaluation but also on objective evaluation,and it is effective at the eliminate of background noise and outstanding at making the saliency regions high light.

关 键 词：感兴趣区域 显著图 GBR 改进FT 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]