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中巴02B卫星多光谱影像中LBV数据变换方法研究
  • 期刊名称:地理与地理信息科学
  • 时间:0
  • 页码:21-25+113
  • 语言:中文
  • 分类:TP75[自动化与计算机技术—控制科学与工程;自动化与计算机技术—检测技术与自动化装置]
  • 作者机构:[1]中国科学院烟台海岸带研究所,中国科学院山东省海岸带环境过程重点实验室,山东烟台264003, [2]中国科学院研究生院,北京100049, [3]河北师范大学,河北石家庄050016
  • 相关基金:国家自然科学基金项目(40801124); 中国科学院知识创新工程项目(KZCX2-YW-224); 中国科学院信息化项目(INFO-115-C01-SDB4-17); 山东省优秀中青年科学家科研奖励基金项目; 河北师范大学自然基金项目
  • 相关项目:基于网格技术海岸带区域气溶胶卫星遥感反演研究
中文摘要:

通过对实际获得的多光谱影像的光谱特征分析,提出了可用于中巴02B卫星多光谱影像的LBV数据变换公式,使得LBV数据变换方法在国产中巴02B卫星数据上的应用成为可能;运用该变换公式处理得到的中巴LBV数据变换图像比中巴原始数据假彩色合成图像颜色更鲜艳,地物类别更易区分,具有更好的目视解译效果。将LBV变换图像与中巴数据假彩色图像分别用最大似然法进行分类,分类图像和精度检验结果表明:用LBV变换公式得到的LBV结果图像能很好地提高图像计算机分类的精度,该变换方法在中巴02B卫星数据的应用中具有很大潜力。

英文摘要:

LBV is a new data transformation method which is recently proposed for remote sensing dada transformation processing,however,it is can′t be directly used to CBERS-02B multi-spectral data since there are relative transformation equations data until now.Based on detailed ground spectral features studies of multi-spectral images from CBERS-02B,new LBV data transformation equations for CBERS-02B multi-spectral image were specially proposed.These new LBV transformation equations made it possible to use the LBV transformation method on the domestic satellites and provided a new method to process CBERS-02B multi-spectral data.Moreover,image transformation and classification experiments were carried out,which results showed that the LBV transformed result images were more vivid and the features of them were more easily to be classified compared with the original false color composite images.Finally,in order to evaluate the performance of this proposed transform method,the maximum likelihood supervised classification method was used to the LBV transformed result images and the original false color composite images,which results demonstrated that the accuracy of the LBV transformed image was obviously better than that of the original false color composite images,which showed that the proposed LBV transform method has good potential for CBERS-02B multi-spectral images processing in the future applications.

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