结合多空间特征的多尺度马尔可夫随机场彩色图像分割  

Color image segmentation of multi-resolutin Markov random field in combination with multi-space characteristics

作　　者：杨华勇[1] 余正红[1] 郑晨[2] 

机构地区：[1]武汉科技大学城市学院信息工程学部,武汉430083 [2]武汉大学数学与统计学院,武汉430072

出　　处：《计算机应用》2011年第12期3378-3381,共4页journal of Computer Applications

摘　　要：提出了一种结合多空间特征的多尺度马尔可夫随机场(MRF)模型———MS-MRMRF。针对RGB单空间对彩色图像描述不足的问题,模型首先将图像转化为HSV空间并与RGB空间结合形成多空间特征;然后根据多空间特征的形式,提出了一种模糊化估参的多尺度MRF模型对其进行分割。彩色图像的分割实验表明:相比现有的单空间特征的多尺度MRF算法,结合多空间特征的多尺度MRF可以有效地提高分割精度。This paper proposed a new Multi-Space Multi-Resolutin Markov Random Field Model（MS-MRMRF）.Concerning the inadequate description of the color images in a single RGB space,the proposed model firstly transformed images from the RGB color space to the HSV color space and combined these two color spaces as a multi-space feature;then a new multi-resolution Markov model was designed to segment the image based on the multi-space feature,which estimated the parameters by fuzzy theory.The experiments of the color images demonstrate that the segmentation results of MS-MRMRF model have a higher segmentation accuracy compared with the segmentation results of multi-resolution MRF with a single RGB space.

关 键 词：图像分割 多空间特征 多尺度 马尔可夫随机场 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]