基于感知编组规则的遥感影像分析马尔柯夫随机场图模型研究

项目名称： 基于感知编组规则的遥感影像分析马尔柯夫随机场图模型研究

项目编号： No.41401409

项目类型： 青年科学基金项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 王琰

作者单位： 生态环境部环境工程评估中心

项目金额： 25万元

中文摘要： 本课题提出了一种基于感知编组规则的遥感影像分析马尔柯夫随机场图模型（MRFG），用以解决高分辨率遥感影像解译中由于像斑外形不规则、空间特征定量化表达困难造成的像斑多特征难以综合分析的问题。研究以感知编组为基础完成空间结构性特征的定量化分析和数学表达，结合已有的光谱特征共同建立特征空间；在此基础上以随机场理论和图论为基础建立马尔柯夫随机场图模型，用以进行像斑的多特征综合分析；同时针对光谱、空间特征表达方式不同的特点设计能量函数并完成模型解算；以土地利用变化检测为实际应用验证和更新模型，从而为地理国情监测领域提供科学方法和理论依据。

中文关键词： 变化检测方法；马尔柯夫随机场；土地利用与土地覆被；光学遥感；知识推理

英文摘要： A Markov Random Field Graph Model (MRFG) for remote sensing image analysis based on perceptual organization rules is introduced in this project, aiming at solving the problem of multi-feature comprehensive analysis of image segments. This problem is caused by the irregular shape of image segments and the difficulty of spatial feature quantitative analysis during object-based high resolution remote sensing image interpretation. Spatial structure features of image segments were analyzed quantitatively and mathematical formulation were given according to perceptual organization rules, and together with other spectral features of image segments the feature space is established. MRFG model is then constructed on the basis of random field and graph theory, used for multi-feature image segment analysis. Meanwhile energy function of MRFG and related model solution method were designed according to the different forms of the features. Land use/cover change detection is selected as a kind of practical applications for experimental verifying and updating the model, so as to provide a scientific method as well as a theoretical foundation in the field of Geographical National Condition Monitoring.

英文关键词： change detection;Markov Random Field;land use and land cover;optical remote sensing;knowledge reasonsing