Multi-focus Image Fusion Based on Fuzzy and Wavelet Transform
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
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A multi-focus image fusion algorithm with Dual-Tree Complex Wavelet Transform (DT-CWT) is proposed in the paper. There are some disadvantages in Discrete Wavelet Transform (DWT), such as shift variance and lack of directional selectivity. Therefore, to have better representation of the images, they are processed with DT-CWT. The low frequency coefficients and high frequency coefficients are fused separately with different methods because of their different characteristics. To the low frequency coefficients, neighborhood gradient maximum selectivity (NGMS) scheme is used, the ones having maximal neighborhood gradient are selected. To the high frequency coefficients, the absolute value maximum selectivity (AVMS) is used, the ones having maximal absolute values are selected. Experiment results show that the algorithm proposed in this paper not only solves the problems such as low contrast and blocking effects caused by fusion algorithms in space domain, but also avoids the artifacts and ringing artifacts exhibited by conventional wavelet based fusion algorithms. Keywords: DT-CWT, image fusion, multi-focus, NGMS, AVMS