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.