【摘要】 采用了HIS ,PCA和HPF三种融合方法对IKONOS全色和多光谱影像进行融合 .从光谱特征、空间特征及融合前后影像的地物分类精度等方面分析了 3种融合结果的质量 .分析评价结果表明HPF融合效果最佳 .该方法在提高多光谱影像空间分辨率的同时 ,较好地保留了多光谱影的光谱信息 ,并能减小阴影的影响 .分析结果还表明PCA融合方法对IKONOS数据融合具有不确定性 ,其融合效果与区域影像特征向量矩阵中第一特征向量有密切的关系 .更多还原

【Abstract】 HIS (hue-intensity-saturation), PCA (principal component analysis), HPF (high pass filtering) are used to fuse IKONOS low-resolution multispectral and high-resolution panchromatic images to achieve both high spatial and spectral resolution in a single image. The three fused images are evaluated both spectrally and spatially, and the influence of image fusion on thematic accuracy of land cover classification is examined. The advantages and degree of improvement in the classification from using fused images are displayed. Analyses show that HPF has the best quality both spectrally and spatially and the shadow of building is reduced. HIS comes second. PCA approach is sensitive for IKONOS image to the choice of area to be analyzed and the fusion effect is related closely with the first eigenvector of the area.更多还原