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Image fusion based on image decomposition using self-fractional Fourier functions

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Image fusion has been receiving increasing attention in the research community in a wide spectrum of applications. Several algorithms in spatial and frequency domains have been developed for this purpose. In this paper we propose a novel algorithm which involves the use of fractional Fourier domains which are intermediate between spatial and frequency domains. The proposed image fusion scheme is based on decomposition of source images (or its transformed version) into self-fractional Fourier functions. The decomposed images are then fused by maximum absolute value selection rule. The selected images are combined and inverse transformation is taken to obtain the final fused image. The proposed decomposition scheme and the use of some transformation before the decomposition step offer additional degrees of freedom in the image fusion scheme. Simulation results of the proposed scheme for different transformation of the source images for two different sets of images are also presented. It is observed through the simulation results that the use of taking the transformation before the decomposition step improves the quality of fused image. In particular the results of using the fractional Fourier transform and discrete cosine transform before the decomposition step are encouraging.

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Correspondence to K. K. Sharma.

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Sharma, K.K., Sharma, M. Image fusion based on image decomposition using self-fractional Fourier functions. SIViP 8, 1335–1344 (2014).

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