Mixed scheme based multimodal medical image fusion using Daubechies Complex Wavelet Transform

Multimodal medical image fusion is an important task for retrieving complementary information from different modality of medical images. Image fusion can be performed using either spatial or transform domain methods. Limitations of spatial domain fusion methods led to transform domain methods. Discrete wavelet transform (DWT) based fusion is one of the most widely used transform domain method. But it suffers from shift sensitivity and does not provide any phase information. These disadvantages of DWT motivated us to use complex wavelet transform. In the present work, we have proposed a new multimodal medical image fusion method using Daubechies complex wavelet transform (DCxWT) which applies two separate fusion rules for approximation and detail coefficients. Shift invariance, availability of phase information and multiscale edge information properties of DCxWT improves the quality of fused image. We have compared the proposed method with spatial domain fusion methods (PCA and linear fusion) and transform domain fusion methods (discrete and lifting wavelet transforms). Comparison of results has been done qualitatively as well as by using different fusion metrics (entropy, standard deviation, fusion factor, fusion symmetry and Q_AB^F). On the basis of qualitative and quantitative analysis of the obtained results, the proposed method is found to be better than spatial domain fusion methods (PCA and linear fusion) and transform domain fusion methods (discrete and lifting wavelet transforms).