Multi-Resolution Image Fusion Algorithm Based on Improved Regional Cross Entropy and Morphology

Abstract:

Based on image contents, the better to simulate the process pattern of human eyes vision, an image fusion method that emphasizing edge preserving is proposed. Through wavelet transform, an improved regional cross entropy fusion rule is used for the low-frequency component which reflects approximate contents, the fusion method for incorporation of the maximum morphology edge measuring and weighted variance analysis is used for the high-frequency component which reflects detail features of image. Finally, the fusion image is reconstructed through an inverse transform of wavelet. Experimental results show that by using this algorithm, the mutual information between the images can be fused organically, the image clarity is raised, the details of fusion image are enhanced, and the edge information are reappeared better. Strong support for the follow-up information analysis and extractive ability of the images are provided.

• Periodical: Advanced Engineering Forum (Volumes 6-7)
• Pages: 589-594
• DOI: https://doi.org/10.4028/www.scientific.net/AEF.6-7.589
• Online since: September 2012
• Authors: Wen Ge, Jin Li Xu, Peng Li
• Keywords: Edge Information, Image Fusion, Morpholoy, Regional Cross Entropy, Wavelet Transform (WT)

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