Volume 8, Issue 3
A Novel Image Fusion Method Via Ratio Weighted and Condition Weighted Based on Shearlet Transform

Weibin Chen, Lai Zhou, Xin Zhang & Hongbin Gu

Journal of Fiber Bioengineering & Informatics, 8 (2015), pp. 625-633.

Published online: 2015-07

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  • Abstract

In this paper, a new image fusion method is proposed based on the shearlet transform. The new image is reconstructed by image fusion, which provides richer visual information than the original images. The image could be decomposed by shearlet transform in any scale and any direction, and the detail information can be caught easily. The multi-scale and multiple directions decomposition coefficients are obtained through shearlet transformation. The fusion results are analyzed and compared with the measurement of human visual system and objective evaluation. The experiment results show the advantages of the new fusion method compare to other classical fusion algorithm. The simulation results of the multimodal images are adopted to demonstrate that the algorithm based on shearlet transform is able to obtain fused images of higher clarity and complementary information compared with any other methods.

  • Keywords

Image Fusion Shearlet Transform Condition Weighted Edge Features

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COPYRIGHT: © Global Science Press

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@Article{JFBI-8-625, author = {}, title = {A Novel Image Fusion Method Via Ratio Weighted and Condition Weighted Based on Shearlet Transform}, journal = {Journal of Fiber Bioengineering and Informatics}, year = {2015}, volume = {8}, number = {3}, pages = {625--633}, abstract = {In this paper, a new image fusion method is proposed based on the shearlet transform. The new image is reconstructed by image fusion, which provides richer visual information than the original images. The image could be decomposed by shearlet transform in any scale and any direction, and the detail information can be caught easily. The multi-scale and multiple directions decomposition coefficients are obtained through shearlet transformation. The fusion results are analyzed and compared with the measurement of human visual system and objective evaluation. The experiment results show the advantages of the new fusion method compare to other classical fusion algorithm. The simulation results of the multimodal images are adopted to demonstrate that the algorithm based on shearlet transform is able to obtain fused images of higher clarity and complementary information compared with any other methods.}, issn = {2617-8699}, doi = {https://doi.org/10.3993/jfbim00118}, url = {http://global-sci.org/intro/article_detail/jfbi/4744.html} }
TY - JOUR T1 - A Novel Image Fusion Method Via Ratio Weighted and Condition Weighted Based on Shearlet Transform JO - Journal of Fiber Bioengineering and Informatics VL - 3 SP - 625 EP - 633 PY - 2015 DA - 2015/07 SN - 8 DO - http://doi.org/10.3993/jfbim00118 UR - https://global-sci.org/intro/article_detail/jfbi/4744.html KW - Image Fusion KW - Shearlet Transform KW - Condition Weighted KW - Edge Features AB - In this paper, a new image fusion method is proposed based on the shearlet transform. The new image is reconstructed by image fusion, which provides richer visual information than the original images. The image could be decomposed by shearlet transform in any scale and any direction, and the detail information can be caught easily. The multi-scale and multiple directions decomposition coefficients are obtained through shearlet transformation. The fusion results are analyzed and compared with the measurement of human visual system and objective evaluation. The experiment results show the advantages of the new fusion method compare to other classical fusion algorithm. The simulation results of the multimodal images are adopted to demonstrate that the algorithm based on shearlet transform is able to obtain fused images of higher clarity and complementary information compared with any other methods.
Weibin Chen, Lai Zhou, Xin Zhang & Hongbin Gu. (2019). A Novel Image Fusion Method Via Ratio Weighted and Condition Weighted Based on Shearlet Transform. Journal of Fiber Bioengineering and Informatics. 8 (3). 625-633. doi:10.3993/jfbim00118
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