Abstract: 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.

Key words: segmentation, multi-space feature, multiresolution, Markov Random Field, fuzzy

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。

关键词: 分割, 多空间特征, 多尺度, 马尔科夫, 模糊