CAJ | 학술논문

选择覆盖内蒙古阿荣旗地区CBERS02-CCD数据,采用直方图匹配法、主成分分析法、矩匹配法、低通滤波法、小波变换法等空间域和频率域共5种方法,结合定性分析和定量计算对比评价,结果表明,小波变换法可以有效去除条带噪声,而且在细节突出方面也存在一定优势;矩匹配法容易改变地物本身的光谱信息,虽然条带去除效果较好,但不适宜CBERS-02影像数据图像与处理工作;主成分分析法不仅没有去除条带,在某种程度上,反而加强了条带噪声.
선택복개내몽고아영기지구CBERS02-CCD수거,채용직방도필배법、주성분분석법、구필배법、저통려파법、소파변환법등공간역화빈솔역공5충방법,결합정성분석화정량계산대비평개,결과표명,소파변환법가이유효거제조대조성,이차재세절돌출방면야존재일정우세;구필배법용역개변지물본신적광보신식,수연조대거제효과교호,단불괄의CBERS-02영상수거도상여처리공작;주성분분석법불부몰유거제조대,재모충정도상,반이가강료조대조성.
Based on the project of land macroscopical monitoring by CBERS, a remote sensing image of Arongqi in Neimonggu region was put into case study by using different methods:histogram matching, principal component analysis, moment matching, low-pass filter and wavelet transform.A qualitative analysis and quantitative assessment were carried out.The results showed that wavelet transform can not only effectively remove the stripe noise, but also keep the details;although moment matching also has a better removal, but change the features of the spectrum itself easily, so it is not fit for CBERS-02 image processing;principal component analysis can not remove stripe noise but strengthen it.