自适应阈值的多光谱遥感影像软硬分类方法研究  

Hard and Soft Classification Method of Multi-Spectral Remote Sensing Image Based on Adaptive Thresholds

作　　者：胡潭高[1] 徐俊锋[1] 张登荣[1] 王洁[1] 张煜洲[1] 

机构地区：[1]杭州师范大学理学院遥感与地球科学研究院,浙江省城市湿地与区域变化研究重点实验室,浙江杭州311121

出　　处：《光谱学与光谱分析》2013年第4期1038-1042,共5页Spectroscopy and Spectral Analysis

基　　金：国家自然科学基金项目(41201458;41101344);国家高技术研究发展计划项目(2006AA120101);杭州师范大学遥感与地球科学研究院开放基金项目(PDKF2012YG05)资助

摘　　要：土地覆盖遥感分类根据图像中每个像元在不同波段具有不同光谱亮度、空间结构特征或者其他差异的特征,按照某种规则或算法提取土地覆盖分类信息。硬分类方法由于混合像元的存在,导致遥感分类和面积测量精度难以达到使用要求;软分类方法能够解决混合像元问题。针对硬分类与软分类各自存在的问题及优势,在分析硬分类模型和软分类模型的理论基础上,通过研究两种模型的优缺点取长补短,优化分类模型。在新的软硬分类方法支持下,设计典型应用案例,在精度评价过程采用改进型混淆矩阵评价方法,验证该方法在土地覆盖信息提取方面的精度。结果表明,软硬分类方法能够有效提高土地覆盖分类精度。Hard and soft classification techniques are the conventional methods of image classification for satellite data,but they have their own advantages and drawbacks.In order to obtain accurate classification results,we took advantages of both traditional hard classification methods（HCM） and soft classification models（SCM）,and developed a new method called the hard and soft classification model（HSCM） based on adaptive threshold calculation.The authors tested the new method in land cover mapping applications.According to the results of confusion matrix,the overall accuracy of HCM,SCM,and HSCM is 71.06%,67.86%,and 71.10%,respectively.And the kappa coefficient is 60.03%,56.12%,and 60.07%,respectively.Therefore,the HSCM is better than HCM and SCM.Experimental results proved that the new method can obviously improve the land cover and land use classification accuracy.

关 键 词：自适应阈值 多光谱遥感影像 软硬分类 土地覆盖 利用 

分 类 号：TP75[自动化与计算机技术—检测技术与自动化装置]