In order to solve the problem of directional finiteness in wavelet transform
and reduce the redundancy of Laplacian pyramid decomposing in contourlet transform
an image fusion algorithm for regional gradient selection mean is proposed
based on the wavelet-based contourlet transform(WBCT).In this algorithm
weighted mean rules are employed for low frequence while for high frequence
the regional gradient is calculated with the use of selection average rules.Evaluation of the experimental results according to objective criteria including spatial frequence
cross entropy and deviation demonstrates that the fusion algorithm based on WBCT is better than the one based on wavelet transform or contourlet transform with the same fusion rules.
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