A new image fusion algorithm based on Wavelet Transform and the Second Generation Curvelet Transform

This paper analyzes the characteristics of the Second Generation Curvelet Transform and put forward an image fusion algorithm based on Wavelet Transform and the Second Generation Curvelet Transform. We looked at the selection principles about low and high frequency coefficients according to different frequency domain after Wavelet and the Second Generation Curvelet Transform. In choosing the low-frequency coefficients, the concept of local area variance was chosen to measuring criteria. In choosing the high-frequency coefficients, the window property and local characteristics of pixels were analyzed. Finally, the proposed algorithm in this article was applied to experiments of multi-focus image fusion and complementary image fusion. According to simulation results, the proposed algorithm hold useful information from source multiple images quite well.

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