Generalized Model for Remotely Sensed Data Pixel-level Fusion and its Implementation Technology

The generalized model characterizing most remotely sensed data pixel-level fusion techniques is very important for theory analysis and application.According to the imaging mechanism and the ideal pan-sharpening results of multi-spectral image,a generalized model for remote sensing data fusion is presented,which can clearly describe the mathematical relationship among original multi-spectral image,the spatial details extracted from high-resolution panchromatic image,and the adopted fusion strategy.Also three types of fusion algorithm are translated into the generalized model using mathematical expression.The implementation technology based on the generalized model is developed,which only calculates the variables affecting the fusion results instead of all variables.Then these calculation methods of the two key variables are listed for most common pixel-level fusion algorithms.Compared to other models,the generalized model is comprehensive and adaptive.Analyzing implementation steps and comparing with the regular fusion results,the implementation technology which can be applied to most fusion algorithms can reduce computation complexity and save calculation time,which is helpful to promote application of remote sensing data fusion.