While there are multiple images obtained by different sensors to measure the same object scene

one new multiscale image fusion algorithm based on probabilistic model is proposed.Its elementary idea is:Firstly

to decompose each sensor image into multiple subimages which compose a multiscale pyramid via wavelet packet transform

and to establish pixel-based subimage model on every level in the pyramid.Secondly

estimate the model parameters using least squares method based on the corresponding pixel of each level of the sensor image.Then

based on the model

derive estimation of the true scene using maximum posterior method.Finally

we may obtain global fusion estimate with the object scene by applying orderly inverse wavelet packet transformation to every local fusion estimate from each level of the pyramid.The result of fusing the visible image and infrared image shows that the proposed algorithm is valid.