%0 Journal Article
%T Scaling Transformation of Remote Sensing Digital Image with Multiple Resolutions from Different Sensors<br>多传感器不同分辨率遥感数字图像的尺度转换
%A BUHE Aosier
%A MA Jianwen
%A WANG Qinxue
%A KANEKO Masami
%A FUKUYAMA Ryuji
%A <br>布和敖斯尔
%A 马建文
%A 王勤学
%A 金子正美
%A 福山龙次
%J 地理学报
%D 2004
%I 
%X In order to acquire high resolution, data fusion technique can be used to combine multiple data from different sensors. This study practices two methods of data fusion: IHS transformation method and wavelet-based method. The result showed that IHS transformation method was a relatively simple one to be used, but it can not remain all information except for three bands of RGB. However, the wavelet-based method is relatively complicated and it can get high resolution images in all bands. As an approach to scale down the resolution of images, a so-called pixel level data scaring model was used in this study. Comparisons were made from data acquired by four multi-spectral sensors (Landsat/ETM , Terra/ASTER, Terra/MODIS, and NOAA/AVHRR) over Kushiro Marsh in Hokkaido, Japan, on September 26, 2001. To reveal the effect of the sensors' spatial resolution, simulated data are generated from the higher spatial resolution (small size pixel) data to match the lower spatial resolution (larger size pixel) data. The result shows that the Terra/ASTER images can be effectively down-scaled to the resolution of Landsat/ETM . However, it is rarely effective to scale down both Landsat/ETM and Terra/ASTER images to the resolution of MODIS and AVHRR.
%K data
%K fusion
%K wavelet-based
%K transformation
%K pixel
%K level
%K data
%K scaring
%K model
%K Hokkaido<br>数据融合
%K 小波变换
%K 像元级的尺度扩展
%K 札幌
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=E62459D214FD64A3C8082E4ED1ABABED5711027BBBDDD35B&cid=869B153A4C6B5B85&jid=F7B5B947C24B9D649491012214E4BEF4&aid=7CA3C43A29435D67&yid=D0E58B75BFD8E51C&vid=6AC2A205FBB0EF23&iid=CA4FD0336C81A37A&sid=74011071555EB4E5&eid=4DB1E72614E68564&journal_id=0375-5444&journal_name=地理学报&referenced_num=11&reference_num=16