ABSTRACT The paper analyses the characteristics of the Fast Discrete Curvelet Transform and put forward an image fusion algorithm based on Discrete Wavelet Transform and the Fast Discrete Curvelet Transform. The Curvelet Transform is a new approach in the image fusion techniques adding a new, lesser redundant, fast and simple way of dealing the images especially at the edges and curves and hence it is very suitable for the analysis of various natural images like Medical images using tomographic images like MRI and CT scan, seismic images, satellite pictures for the weather monitoring etc. The experimental results show that the method could extract useful information from the source images to fused images so that clear images are obtained. In choosing the low-frequency coefficients, the concept of local area variance was applied to the measuring criteria. In choosing the high frequency coefficients, the window property and local characteristics of pixels were analysed. Finally, the proposed algorithm was applied to experiments of multi-focus image fusion and complementary image fusion
