Sum-modified-Laplacian-based Multifocus Image Fusion Method in Sharp Frequency Localized Contourlet Transform Domain
Sum-modified-Laplacian-based Multifocus Image Fusion Method in Sharp Frequency Localized Contourlet Transform Domain
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发表时间：
2008
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通讯作者：
Xiao-bo Qu;Jingwen Yan
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作者：
Xiao-bo Qu;Jingwen Yan
In order to suppress pseudo-Gibbs phenomena around singularities of fused image and reduce significant amount of aliasing components which are located far away from the desired support when the original contourlet is employed in image fusion, Sum-modified-Laplacian-based multifocus image fusion method in sharp frequency localized contourlet transform (SFLCT) domain is proposed. First, SFLCT, instead of the original contourlet, is utilized as the multiscale transform to decompose the source multifocus images into subbands. Second, typical measurements for multifocus image fusion in spatial domain are introduced into contourlet domain and Sum-modified-Laplacian (SML), evidenced in this paper with the best capability to distinguish SFLCT coefficients is from the clear parts or blurry parts of images, is employed in SFCLT subbands as measurement to select SFLCT transform coefficients. Third, inverse SFLCT is used to reconstruct fused image. Finally, cycle spinning is applied to compensate for the lack of translation invariance property and suppress pseudo-Gibbs phenomena of fused images. Using the proposed fusion method, experimental results demonstrate that mutual information is improved by 5.87% and transferred edge information Q is improved
