摘要
针对运用信息熵测度度量遥感影像信息量存在的信息冗余问题,基于马尔科夫随机场模型研究了一种顾及空间相关的遥感影像信息测度方法。该方法对传统马尔科夫随机场进行简化,将这种简化的马尔科夫随机场模型应用于影像信息熵的计算。对该方法的计算公式进行了推导,证明了其可以减弱空间相关给影像信息熵测度造成的信息冗余,并且不需要进行高维计算。实验验证了这种空间熵对影像信息度量的有效性。
In this paper,an information measurement has been researched based Markov random field. This measurement can reduce the information redundancy caused by spatial correlation. In this method, a simple Markov random field is used to compute information entropy of remotely sensed imagery. Theoretically,the compute equations have been derived,and the highdimension computation is not needed. Experimental results prove the effectiveness of the proposed method.
作者
刘凤珠
杨伯钢
张飞舟
杨应
LIU Fengzhu;YANG Bogang;ZHANG Feizhou;YANG Ying(School of Earth and Space Sciences,Peking University,Beijing 100871,China;Beijing Institute of Surveying and Mapping,Beijing 100038,China;Beijing Key Laboratory of Urban Spatial Information Engineering,Beijing 100038,China;National Geomatics Center of China,Beijing 100830 China)
出处
《遥感信息》
CSCD
北大核心
2018年第2期9-16,共8页
Remote Sensing Information
基金
城市空间信息工程北京市重点实验室经费资助项目(2017207)
测绘地理信息公益性行业科研专项项目(201512010)
关键词
遥感影像
信息量
信息熵
马尔科夫随机场
空间相关
remotely sensed imagery
information
entropy
Markov random field
spatial correlation
