Novel Masks for Multimodality Image Fusion using DTCWT

Fusion is basically extraction of best of inputs and conveying it to the output. In this paper, we present an image fusion technique using the dual tree complex wavelet transform (DT-CWT). We have proposed novel masks to extract information from the decomposed structure using DT-CWT. The main goal of this paper is to introduce a new approach to fuse multimodality images using dual tree complex wavelet transform. Experiment results show that the proposed fusion method based on complex wavelet transform is remarkably better than the fusion method based on classical discrete wavelet transform. This method is relevant to visual sensitivity and tested by merging multisensor, multispectral and defocused images apart from CT and MR images. Fusion is achieved through the formation of a fused pyramid using the DTCWT coefficients from the decomposed pyramids of the source images. The fused image is obtained through conventional inverse dual tree complex wavelet transform (DTCWT) reconstruction process. Results obtained using the proposed method show a significant reduction of distortion.

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