摘要
提出了一种基于颜色空间的Local特征和Regional特征的自然图像显著性检测方法.该方法将图像分成8×8的子块,计算多个尺度下每一个子块的Local特征和Regional特征,并将其加权组合来确定子块的显著程度,从而得到整个图像的显著特征.此外,通过计算4个颜色通道上的色度对比度,获得显著物体的边缘.将图像的显著特征与显著物体的边缘综合后得到图像中的显著目标.实验结果显示,本文提出的方法能够快速、清晰而准确地提取出图像中的显著性目标.
This paper proposes a model o5 salient reglon detection based on local and regional features m color space. Firstly, the image is divided into 8 × 8 sub-blocks, in each sub-block, then the multi-scale local and regional features are calculated and combined by weighted summation as the sub-block＇s salient value; secondly, the salient edge is calculated by the color contrast of the four color channels; finally~ the salient map can be extracted by combining the salient features and salient edge together. The experiment resu]ts show that our model can extract salient objects in images fast and exactly.
出处
《自动化学报》
EI
CSCD
北大核心
2013年第8期1214-1224,共11页
Acta Automatica Sinica
基金
国家自然科学基金(60302018)
河北省科技支撑计划项目(11213518D)资助~~
