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在南方水稻遥感监测中,单一传感器影像数据已不能满足监测精度的要求,需要将高空间分辨率全色影像与中高空间分辨率多光谱影像进行融合,得到新的高空间分辨率多光谱影像,有利于改善影像识别与分类精度.该文利用江苏省金湖地区HJ-1A卫星30m分辨率多波段影像与ALOS卫星2.5m分辨率全色影像进行水稻监测,采用4种融合方法(Brovey变换、IHS变换、高通滤波和小波变换)对2种影像进行融合处理.随后对各种融合影像结果进行了目视定性和融合评价指标定量说明与评价,结果表明小波变换在空间与光谱信息上具有最佳的融合效果.进一步利用小波变换的融合影像进行水稻识别与面积提取,统计表明融合影像相比HJ-1A多光谱影像,水稻面积估测精度从79.26%提高到91.65%.因此,利用多源遥感数据融合的方法对南方水稻面积进行监测,可显著提高其监测精度.
In the remote sensing monitoring of rice in the south, the single sensor image data can not meet the requirements of monitoring accuracy. The high spatial resolution panchromatic image needs to be fused with the mid-high spatial resolution multispectral image to obtain a new high spatial resolution multispectral image, Which will help to improve the accuracy of image recognition and classification.This paper uses the 30m resolution multi-band image of HJ-1A satellite and the 2.5m resolution panchromatic image of ALOS satellite in Jinhu area of Jiangsu Province for rice monitoring. Four kinds of fusion methods (Brovey transform, IHS transform, high-pass filter and wavelet transform) are used to fuse the two kinds of images.Afterwards, the qualitative and quantitative evaluation indices of the fusion images are quantitatively described and evaluated. The results show that the wavelet transform has the most spatial and spectral information The results show that the accuracy of the rice area estimation is improved from 79.26% to 91.65% compared with the HJ-1A multi-spectral image, so the multi-source Remote sensing data fusion method to monitor the rice area in the South can significantly improve its monitoring accuracy.