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Innovative Multilevel Image Fusion Algorithm using Combination of Transform Domain and Spatial Domain Methods with Comparative Analysis of Wavelet and Curvelet Transform

fusion is widely used term in different applications namely satellite imaging, remote sensing, multifocus imaging and medical imaging. In this paper, we have implemented multi level image fusion in which fusion is carried out in two stages. Firstly, Discrete wavelet or Fast Discrete Curvelet transform is applied on both source images and secondly image fusion is carried out with either spatial domain methods like Averaging, Minimum selection, maximum selection and PCA or with Pyramid transform methods like Laplacian Pyramid transform. Further, comparative analysis of fused image obtained from both Discrete Wavelet and Fast Discrete Curvelet transform is done which proves effective image fusion using proposed Curvelet transform than Wavelet transform through enhanced visual quality of fused image and by analysis of 7 quality metrics parameters. The proposed method is very innovative which can be applied to medical and multifocus imaging applications in real time. These analyses can be useful for further research work in image fusion and also the fused image obtained using Curvelet transform can be helpful for better medical diagnosis.