Image Fusion Based on Integer Lifting Wavelet Transform

Image fusion can synthesize many images from different sensors into a picture which can meet specific application by using a mathematical model. It can effectively combine the advantages from different images and improve the analysis ability (Blum et al., 2005). In recent years, the image fusion in automatic target recognition, computer vision, remote sensing, robots, medical image processing and military fields has a very wide range of applications. In many of the image fusion technology, image fusion based on multi-resolution analysis has become the focus of research and hotspot now. At present, the image fusion base on multi-resolution method can be divided into three kinds(Hu et al., 2008): the first kind is based on the pyramid decomposition (such as Laplace pyramid, ratio low-pass pyramid, contrast pyramid, gradient pyramid, etc.). The second type is based on wavelet decomposition, such as discrete wavelet transform(Li &Wu, 2003), wavelet and wavelet packet framework(Wang, 2004), multi-wavelet transform(Zhang et al., 2005), integer wavelet transform(Wang et al., 2008), FILWT (Li&Zhu, 2007), the dual tree complex wavelet transform(Yang et al., 2007), etc. The third type is new multiresolution methods, such as image fusion based on finite ridgelet transform(Liu et al., 2007), curvelet transform(Filippo et al., 2007) and contourlet transform(Li et al., 2008; Yang & Jiao, 2008) . In the multi-resolution fusion process, the choices of rules and operators is crucial and it will affects the quality of fusion image. However, the existing multiresolution image fusion research and experiment are basically only for two images and the model is only suitable for 2 image fusion. It cannot be generalized to many images (two above ) fusion. Although in the multiresolution image fusion methods, the existing simple fusion rules model can be extended to the fusion which has more than two image. Such as average accurate measurement, pixel absolute value choose big quasi measurement and based on region characteristics (such as regional energy, entropy, variance, average gradient, contrast and markov distance etc) choice of large prospective measurement, etc, but the result is very limited. Therefore, this paper, a novel fusion algorithm of multiple images based on fast integer lifting wavelet transform is proposed. The algorithm may consider both of the result and speed of the fusion with tools of lifting wavelet. Also, according to the image promotion wavelet transformation different sub-bands characteristics, two kinds of new high and low