异源、同源传感器影像融合的比较研究

遥感影像的融合是遥感界的一个研究热点。根据数据源的不同，影像融合可分为异源传感器影像融合和同源传感器影像融合。以TM与SPOT作为异源影像融合的例子，以IKONOS的MS与Pan作为同源影像融合的例子，用5种算法对两种融合类型进行实验与比较。结果表明，同源传感器影像的融合效果好于异源传感器影像的融合效果；不同的融合算法在异源和同源传感器影像融合中的表现不尽相同。SVR变换可同时应用于异源及同源传感器影像的融合，且在提高影像空间分辨率、信息量和清晰度的同时能很好地保持原始多光谱影像的光谱特征。SFIM虽然也可以在两种数据源的融合实验中获得较好的融合效果，但其高频信息融入度最差。MB虽然提高了融合影像的高频信息融入程度，但光谱保真度、信息量和清晰度却不理想。Ehlers适用于异源传感器影像间的融合，而WT则适用于同源传感器影像的融合。

Study on the Camparison of Image Fusion for the Same-source and Different-source Sensor

Satellite image fusion is always a focus in remote sensing field.According to data sources difference,image fusion can be divided into two broad categories:fusion of images using different sensors data and using same sensor data.Five recently proposed/modified fusion algorithms have been employed to test the fusion results of the two categories.The image pair,TM+ SPOT pan,was used to test fusion between different image sources,while the pair,IKONOS MS+ pan,was employed to test fusion between same sensor data.The study reveals that the overall results of fusion between same sensor data are better than those of fusion between different sensors image sources.The selected fusion algorithms have different performance in image fusion results between the two categories.The SVR transform is suitable for both categories of image fusion.It can greatly improve the spatial resolution,information quantity and clarity,but retain spectral information of the original multispectral image.The SFIM\|fused image has the highest spectral fidelity in both categories of image fusion,but has the lowest spatial frequency information gain.Although the MB transform can improve the spatial resolution of the original image,it generally failed to improve spectral fidelity,information quantity and clarity.The Ehlers transform is more suitable for image fusion between different sensors data while the WT is more applicable to image fusion between same sensor data.