Abstract: This paper discusses EM algorithm and Bootstrap
approach combination applied for the improvement of the satellite
image fusion process. This novel satellite image fusion method based
on estimation theory EM algorithm and reinforced by Bootstrap
approach was successfully implemented and tested. The sensor
images are firstly split by a Bayesian segmentation method to
determine a joint region map for the fused image. Then, we use the
EM algorithm in conjunction with the Bootstrap approach to develop
the bootstrap EM fusion algorithm, hence producing the fused
targeted image. We proposed in this research to estimate the
statistical parameters from some iterative equations of the EM
algorithm relying on a reference of representative Bootstrap samples
of images. Sizes of those samples are determined from a new
criterion called 'hybrid criterion'. Consequently, the obtained results
of our work show that using the Bootstrap EM (BEM) in image
fusion improve performances of estimated parameters which involve
amelioration of the fused image quality; and reduce the computing
time during the fusion process.