Abstract
We propose an image fusion algorithm based on modified regional consistency and similarity weighting to fuse two multi-focus images with strict registration of the same scene. The algorithm decomposes source image with the shift-invariant discrete wavelet transform (SIDWT) and obtain high frequency components and low frequency component. The regional energy consistency is used in high frequency fusion. The saliency map of multi-focus images is calculated with spectral residual (SR), and combine the similarity weighting method to fuse low frequency coefficient. The simulation results show that the improved algorithm is an effective image fusion algorithm. In terms of visual effects, fusion image keeps details and advances the vagueness. Compared with fusion algorithms based on regional consistency and similarity weighting, its objective evaluation indicators, such as standard deviation and mutual information are also improved.
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Yang, T., Fang, P. (2018). An Image Fusion Algorithm Based on Modified Regional Consistency and Similarity Weighting. In: Zhou, J., et al. Biometric Recognition. CCBR 2018. Lecture Notes in Computer Science(), vol 10996. Springer, Cham. https://doi.org/10.1007/978-3-319-97909-0_27
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DOI: https://doi.org/10.1007/978-3-319-97909-0_27
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