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The fusion algorithms are data-intensive and computation-intensive, whose processing performance is low if commonimplementation techniques are adopted. This paper presents a parallel implementation framework based on a generalized fusionmodel and parallel computing for remotely sensed image fusion. The steps in the implementation corresponding to each fusionalgorithm are mainly the same, which discard the process steps, input and output I/Ooperations not impacting the last results. Theparallel processing mechanism adopts the data decomposition strategies where different data blocks can be processed in differentCPU cores. The developed software module shows that the framework can be applied to implement many algorithms which usuallyare divided into three general categories. The experiments show that the parallel implementation framework is high performance,which not only decreases the processing time in single CPU core environment but also efficiently utilizes the resources of multi-coresin computer

A PARALLEL IMPLEMENTATION FRAMEWORK FOR REMOTELY SENSED IMAGE FUSION