The purpose of image fusion is to obtain an
iamge from multiple images, this image should be able to
reflect the important information of all original images.
Contourlet transform, not only has characteristics of multiresolution locality and critical sampling which wavelet
has but also has the characteristics of multiple
decomposition directions and anisotropy which wavelets
lacking. Energy is a statistical parameter of describe the
texture feature. So we apply the Max Energy and
Contourlet transform combined for image fusion. Entropy
expreses the average amount of information. The distribution of
standard deviation reflects the degree of dispersion of the
image.The average gradient reflects the clarity of the image, the
contrast of small details and the feature of texture transform.
Contrast with wavelet transform, laplace transform,
weighted transform, the traditional of contourlet transform,
on evaluation by Entropy, standard deviation and average
gradient, experimental results from this algorithms for
fusion with infrared image and visual image were better
than other algorithms.