Feature-Based Image Fusion with a Uniform Discrete Curvelet Transform

摘要

Abstract The uniform discrete curvelet transform (UDCT) is a novel tool for multiscale representations with several desirable properties compared to previous representation methods. A novel algorithm based on UDCT is proposed for the fusion of multi-source images. A novel fusion rule for different subband coefficients obtained by UDCT decomposition is discussed in detail. Low-pass subband coefficients are merged to develop a fusion rule based on a feature similarity (FSIM) index. High-pass directional subband coefficients are merged for a fusion rule based on a complex coefficients feature similarity (CCFSIM) index. Experimental results demonstrate that the proposed algorithm fuses all of the useful information from source images without introducing artefacts. Compared with several state-of-the-art fusion methods, it yields a better performance and achieves higher efficiency.