摘要
为快速准确地提取图像中的显著性区域,提出一种改进图割的显著性区域检测算法。采用改进的图割算法对图像进行预分割,将图像分成若干子区域,在此基础上利用区域间对比度计算各区域的显著性值,得到图像的显著图,利用迭代阈值分割算法对图像显著图进行分割处理,通过图像去噪完整有效地提取出显著性区域。实验结果表明,该算法能够准确地提取出图像中的显著性区域,与传统方法相比,使用该算法提取出的显著性区域更完整、准确,提高了效率。
To detect the salient region quickly and accurately in the image ,the improved algorithm of salient region detection based on graph cuts was put forward .Firstly ,the improved graph cuts method was used to pre‐segment the image which was then divided into several sub areas .On this basis ,the regional contrast was used to calculate the salient value of each area which represented the salient map of image .Then the iterative threshold segmentation algorithm was used to segment the image salient map ,the salient region was extracted completely and effectively after image denoising .Experimental result shows that the im‐proved salient detection algorithm can extract the salient region accurately and completely ,it also promotes the efficiency .
出处
《计算机工程与设计》
北大核心
2015年第6期1560-1564,共5页
Computer Engineering and Design
基金
重庆市科委自然科学计划基金项目(2010BB2399)
关键词
显著性区域检测
区域对比度
图割
迭代阈值分割
图像去噪
salient region detection
regional contrast
graph cut
iterative threshold segmentation
image denoising
