项目名称: 基于几何划分和层次结构模型的高分辨率遥感影像分割方法研究
项目编号: No.41301479
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 天文学、地球科学
项目作者: 赵泉华
作者单位: 辽宁工程技术大学
项目金额: 25万元
中文摘要: 随着空间分辨率的提高,遥感影像中像素光谱测度空间相关性更加复杂,因此合理建模这种相关性是高分辨率遥感影像精准分割的关键因素。项目以建立高分辨率遥感影像像素光谱测度空间相关性层次结构模型这一科学问题为核心,对高分辨率遥感影像精准分割算法展开深入的理论与实践研究,实现精度高、可靠性强的高分辨率遥感影像分割。在随机几何、随机场以及贝叶斯等理论基础上,项目重点研究(1)影像域几何划分、地物目标形状的几何表达、像素光谱测度在邻域级、区域级、全局级的统计分布规律,以建立遥感影像的层次结构模型;(2)高分辨率遥感影像分割模型;(3)可变维状态空间的模型参数估计算法;(4)遥感影像分割算法收敛性;(5)影像分割结果验证及评价方法。项目研究成果将给出普适的高分辨率遥感影像空间相关性建模方法学,并将其融入到遥感影像分割算法的设计中,为高分辨率遥感影像的精准解译提供一种新思路。
中文关键词: 几何划分;层次结构模型;高分辨率;遥感影像分割;可逆跳马尔科夫链蒙特卡洛
英文摘要: The last generation satellite data acquiring systems increasingly provide high spatial resolution remote sensing images. The availability of high spatial resolution remote sensing images makes it possible to describe and map the Earth surface both with great geometrical precision and a high level of thematic detail. On the other hand, the increases of geometrical noise and internal spectral variability of each land cover and land use class caused by the improvement in spatial resolution completely changes the perspective of remote sensing image analysis compared with moderate resolution remote sensing image provided by previous-generation remote sensing data acquiring systems. To address the development of novel techniques for the segmentation of high spatial resolution remote sensing image, the research of this project will focus on (1) tessellation based hierarchical model of high spatial resolution remote sensing image, (2) Bayes theory based high spatial resolution remote sensing image segmentation model, (3) parameter estimation scheme for simulating the above image segmentation model, (4) convergence analysis, and (5) evaluation of results. This project proposes a novel region and statistic distribution based method for the segmentation of high spatial resolution remote sensing image. The proposed method i
英文关键词: Geometry Tessellation;Hierarchical Model;High Resolution;Remote Sensing Image Segmentation;Reversible Jump Markov Chain Monto Carlo