Optimum image fusion technique for ALOS data

Image fusion is an effective approach to integrate disparate and complementary information of multi-source imagery. How to keep the spectral information while improving the spatial resolution during the fusion process has always been the research focus. As a new type of remote sensing data source, the lately launched ALOS has three sensors on board and its data can be widely used in the fields of surveying and mapping, precise regional land cover observation, disaster monitoring, resources investigation, etc. Image fusion provides the means for effectively integrating and using different and complementary information from different sensors of ALOS. This paper selects the most commonly used and the most predominant image fusion methods for the fusion of data from ALOS PRISM sensor and data from ALOS AVNIR-2 sensor. It comprehensively evaluates the performance of each method by qualitative and quantitative comparison and analysis, then draws the conclusion that HPF is the most effective method for the fusion of ALOS data; while it greatly improves the spatial resolution, the spectral information is preserved to the maximum extent.