南京信息工程大学学报2018，Vol.10Issue(1)：123-130,8.DOI:10.13878/j.cnki.jnuist.2018.01.012
基于空-谱先验条件随机场的高分辨率遥感影像变化检测方法
Change detection based on conditional random field model with spectral-spatial prior information for high spatial resolution remote sensing imagery
摘要
Abstract
In this paper,a conditional random field model based on spectral-spatial prior information(SSPCRF) is proposed to perform the task of change detection for high spatial resolution remote sensing images.The proposed method firstly introduces a saliency based sample selection strategy which considers the spectral-spatial information of observed difference image to improve the accuracy of modeling initial change detection result.Then a pairwise po-tential with boundary constraint is used to help keep the boundary of changed objects.Finally an inference method based on loopy belief propagation (LBP) algorithm is introduced to perform efficient optimization of the proposed model and get the final change map.The proposed SSPCRF model can greatly improve change detection accuracy while keeping detailed boundary information of changed objects.The proposed method is tested on two high resolution datasets and outperforms the commonly used change detection methods.关键词
变化检测/条件随机场/高空间分辨率/空-谱先验/显著性检测Key words
change detection/conditional random field/high spatial resolution/spectral-spatial prior/saliency de-tection分类
天文与地球科学引用本文复制引用
吕鹏远,钟燕飞,赵济,张良培..基于空-谱先验条件随机场的高分辨率遥感影像变化检测方法[J].南京信息工程大学学报,2018,10(1):123-130,8.基金项目
国家自然科学基金优秀青年基金( 41622107 ) （ 41622107 ）
国家重点研发计划(2017YFB0504202) （2017YFB0504202）
国家自然科学基金(41771385) （41771385）
