基于ICA的遥感图像的色彩分类方法  

Classification of Remote Sensing Image Based on Independent Components Analysis

作　　者：赵蔷[1] 刘淑英[1] 李红[1] 

机构地区：[1]咸阳师范学院信息工程学院,陕西咸阳712000

出　　处：《航空计算技术》2013年第6期5-8,共4页Aeronautical Computing Technique

基　　金：陕西省教育厅专项科研计划项目(09JK811);咸阳师范学院专项科研基金资助项目(11XSYK329)

摘　　要：根据独立成分分析(ICA)方法和多频谱卫星遥感图像的特点,提出了一种基于ICA的遥感图像色彩分类法。方法使用Fast ICA算法提取遥感图像的色彩独立成分,是RGB反转的结合,具有互补的分布,不受照明的影响。使用最大相似度分类算法对像素进行色彩分类,实验结果表明,方法的色彩分类效果较好,对多频谱遥感图像进行色彩分类十分有效。This article propose a classification algorithm for satellite remote sensing images based on Inde- pendent Components Analysis（ICA）. The algorithm combines the advantage of ICA and muhispectral re- motely sensed images. The algorithm extracts the spectral independent components of multispectral re- , motely sensed images by Fast ICA algorithm. It is the combine of reversion about R, G and B, has comple- mentary distribution and is unacted on illumination. Maximum Likelihood is used to classify the pixels. Experimental results demonstrate that the algorithm is an effective improve method to classify the multi- spectral remotely sensed images.

关 键 词：独立成分分析 遥感图像 分类 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]