张满 颜普
摘要:该文提出了一种基于图割和支持向量机(SVM)的彩色遥感图像分割算法,首先针对在RGB空间中很难有效区分颜色相似性的问题,通过选择更加符合颜色视觉特性的HSI颜色空间进行图像处理与分析,然后利用图割算法定义一个能量函数来判断图像中像素是属于图像前景还是图像背景,从而有选择的提取前景种子节点与背景种子节点。最后以前景种子节点与背景种子节点为SVM算法的训练集对遥感图像进行训练分类,完成图像的分割。实验表明此方法是一种有效的彩色遥感图像分割方法。
关键词:图像分割;支持向量机;图割图论;HIS
中图分类号:TP391文献标识码:A文章编号:1009-3044(2012)16-3958-04
A Color Remote Sensing Image Segmentation Algorithm Based on Graph Cut and Support Vector Machine
ZHANG Man,YAN Pu
(Key Lab Intelligent Computing & Signal Ministry of Education,Anhui University, Hefei 230039,China)
Abstract:A color remote sensing image segmentation algorithm based on graph cut and support vector machine is proposed in this paper. Firstly, because it is difficulty to evaluate the similarity of two colors from their distance in RGB color space, color image processing is im? plemented in Hue Saturation Intensity (HSI) space which reflects the features of human vision. Secondly, An energy function is defined by graph cut algorithm for determining the image pixels belongs to the image background image and the prospects,then prospects seed nodes and background seed nodes are used as training set of SVM.Finally, remote sensing image are classified using SVM. A color remote sensing image segmentation is completed. Experiments show the efficiency of the proposed algorithm on color remote sensing images.
Key words:Image Segmentation; Support Vector Machine (SVM); Graphic Theory and Graph Cut; HIS
在对图像的研究和应用中,人们往往仅对图像中的某些部分感兴趣,这些部分常称为目标或前景(其他部分称为背景),它们一般对应图像中特定的具有独特性质的区域。图像分割就是把图像空间划分成若干个具有某些一致性属性的不重叠区域并提取出感兴趣目标的技术和过程,而对图像空间的划分建立在区域的相似性和非连续性基础上。相似性就是说同一区域中的像素特征是类似的;非连续性表明不同区域间像素的特征存在突变。
图像分割是从图像中分割出感兴趣的区域。典型的图像分割算法包括基于区域的算法[1-3]和基于轮廓的算法[4-6],而基于图论的图像分割技术是近年来图像分割领域的一个研究热点[7-9]。遥感图像具有数据量大、模糊性较强、纹理细节丰富等特点,这就决定了无论在分割效率还是分割效果上都对遥感图像的分割提出了比自然景色图像分割更高的要求。……