地理空间信息2024，Vol.22Issue(6)：34-38,5.DOI:10.3969/j.issn.1672-4623.2024.06.008
一种改进的马尔可夫随机场遥感图像分割方法
Remote Sensing Image Segmentation Method Based on Improved Markov Random Field
摘要
Abstract
For traditional Markov random field,the prior parameters in the potential energy function of prior energy are usually manually select-ed based on experience.The distance between pixels is not considered,and the local neighborhood prior features of image are not fully consid-ered.In view of the above problems,we proposed a method of dynamically estimating the prior parameters by combining the prior features of la-bel field and the distance of pixels,which defined the influence coefficient between the pixels of observation field in the prior energy,and intro-duced the Sobel operator into the likelihood energy function to describe the relationship between the pixels of observation field,and combined with the watershed algorithm to eliminate small areas of debris to further optimize the segmentation results.We carried out the relevant experi-ments on the scene classification dataset of Merced Land Use Dataset.The result shows that the method can be effectively applied to remote sens-ing image segmentation.关键词
马尔可夫随机场/分水岭算法/贝叶斯法则/混淆矩阵/遥感图像分割Key words
Markov random field/watershed algorithm/Bayesian rule/confusion matrix/remote sensing image segmentation分类
天文与地球科学引用本文复制引用
袁鹏,刘芳,朱永泰,肖坚,王珂..一种改进的马尔可夫随机场遥感图像分割方法[J].地理空间信息,2024,22(6):34-38,5.基金项目
国家自然科学基金资助项目(41771358) （41771358）
中央高校业务费资助项目(B210202011) （B210202011）
广东省水利科技创新项目(2020-04) （2020-04）
中央高校业务费资助项目(B210202011). （B210202011）
