ZY-3 (Ziyuan-3) satellite is China's first civil high resolution mapping satellite that can provide services for precision agriculture in our country in real-time and steadily. Based on ZY-3 satellite panchromatic images with 2.1 m spatial resolution and multispectral images with 5.8 m resolution data, the methods of image enhancement on ZY-3 agricultural land data were analyzed, taking agricultural land in the Caidian district of Wuhan, Hubei province as an example. The study used different fusion methods such as HSV transformation, Brovey transformation, Gram-Schmidt spectral sharpening, PC spectral sharpening, Wavelet transformation, and Ehlers transformation, all of which are frequently used. For assessing the performance and effect of these fusion methods, the image quality of the fused image was evaluated by qualitative and quantitative analysis. Qualitative analysis relied on visual contrast. To improve the spatial resolution and keep the original image spectrum information of fusion images, two kinds of statistical aspects: grey scale statistics and texture characteristics of different areas, were analyzed quantificationally. Grey scale statistics included correlation index and spectral angle index. Texture characteristics included entropy index, second moment index, and edge response index. In order to better determine the fusion image’s texture features, three block areas of which the spatial structure’s complexity was different from each other, such as building area, farmland, and water, were chosen to analyze their entropy and second moment indexes. Furthermore, through the object-oriented classification method, fusion images were classified into six classes to evaluate the performance of the fusion method at the information level. The six classes included water, arable land, woodland, buildings, bare land, and unclassified. In order to further verify the accuracy of classification, the study used the same methods and parameters to analyze other images of the Wuhu province. Based on the above content, this paper analyzed the applicability of 6 common fusion methods for ZY-3 panchromatic and multispectral agricultural land images. Experiments showed that PC transformation and Ehlers transformation had high spectral fidelity, rich spatial information, and high classification accuracy simultaneously. Brovey transformation and HSV transformation lost serious spectral information, and Brovey transformation also lost great spatial information. The overall classification accuracy of Brovey transformation was poor, but the HSV transformation was good. For GS transformation, the overall analysis result of the classification analysis was bad, but the image quality performed well. The Wavelet transformation lost serious high frequency information, but its spectral fidelity kept well, as did its classification result. Classification experiments introduced details that Brovey transformation was suitable for extracting water. PC transformation, GS transformation, and Wavelet transformation were suitable for building information. For arable land information, priority could be given to Ehlers, PC, and Wavelet transformations. For woodland extraction, Ehlers and Wavelet transformations had better accuracy. HSV transformation was suitable for the extraction of bare land. It is noteworthy that different fusion methods have different advantages in image quality and features extraction. Based on the above reasons, we can select relevant fusion algorithms combined with the practical agriculture application and image information. Comparing experiment data comprehensively, the effects of PC transformation and Ehlers transformation are superior to that of other fusion algorithms, suitable to be applied in ZY-3 panchromatic and multispectral agricultural land data.%针对目前农业部门常用融合方法，探讨适合于ZY-3卫星农业区影像的融合方法，该文以ZY-3卫星2.1 m全色/5.8 m多光谱分辨率平面影像为数据源，应用HSV变换（hue-saturation-value，颜色空间变换）、Brovey变换（彩色标准化变换）、Gram-Schmidt变换（正交化变换）、PC变换（principal components，主成分变换）、Wavelet变换（小波变换）和Ehlers变换（空间滤波变换）等6种常用融合方法，从提高空间分辨率和保持原始图像光谱信息的角度，通过两类统计参数：光谱分析和不同地域的纹理特征，对融合后的影像进行质量评价。通过面向对象方法对融合影像分类比较，全面探讨这6种融合方法对ZY-3卫星农业区影像的适宜性。试验表明，PC变换和Ehlers变换各波段与原多光谱影像相关性均高达0.9以上，纹理特征增强明显，边缘响应指标均高于0.2，分类总体精度分别达78.59%、77.8%；其他融合方法仅在部分试验指标中具有优势。综合比较试验数据，发现PC变换和Ehlers变换融合效果优于其他融合算法，适宜应用于ZY-3卫星农业区影像；但不同融合方法在图像质量和地类提取中各有优势，可结合实际农业应用及影像中地类信息比例，选择适宜的融合算法。该研究可为农业各部门中影像大规模的融合应用提供参考。
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