于嵘, 邓小炼, 王长耀, 张增祥, 亢庆. 基于优化点匹配模式的农作区遥感影像融合分类[J]. 农业工程学报, 2005, 21(11): 95-98.
    引用本文: 于嵘, 邓小炼, 王长耀, 张增祥, 亢庆. 基于优化点匹配模式的农作区遥感影像融合分类[J]. 农业工程学报, 2005, 21(11): 95-98.
    Yu Rong, Deng Xiaolian, Wang Changyao, Zhang Zengxiang, Kang Qing. Classification of romote sensing images of farming areas using resolution fusion algorithm based on optimized point matching[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(11): 95-98.
    Citation: Yu Rong, Deng Xiaolian, Wang Changyao, Zhang Zengxiang, Kang Qing. Classification of romote sensing images of farming areas using resolution fusion algorithm based on optimized point matching[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2005, 21(11): 95-98.

    基于优化点匹配模式的农作区遥感影像融合分类

    Classification of romote sensing images of farming areas using resolution fusion algorithm based on optimized point matching

    • 摘要: 利用遥感影像进行农作物长势监测及估产中,对所用多源影像进行恰当的影像融合是正确解译的重要前提,在传统的基于灰度的影像匹配融合模式中,存在着高运算量和精度不高的问题,该文使用一种基于优化点匹配模式进行农作区遥感影像融合方法,对不同传感器的两景西北农作区遥感影像进行了融合分析验证。所用两景ASTER和SPOT图像匹配总体误差RMS=0.8965,融合后的影像总体分类精度提高到89.67%。

       

      Abstract: There are some shortages of traditional image resolution merge algorithm based on point matching, such as huge quantity of calculation, a little low accuracy, and too many restrictions of application. In order to solve these problems, an optimized remote sensing image matching algorithm was introduced in this paper. Moreover, a comparison experiment on traditional and modified image matching algorithm was performed with an ASTER image and a SPOT image. According to the accuracy comparison of classified image, which increased from 81% to 89%, it can be concluded that the modified algorithm is superior to the traditional algorithm, it has much higher accuracy and efficiency than the latter, and it should have more adaptability and applicable value.

       

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