Image fusion based on shearlet transform and region characteristics

ZHENG Wei; SUN Xueqing; LI Zhe

doi:10.7510/jgjs.issn.1001-3806.2015.01.010

In order to improve the performance of multi-modality medical image fusion and multi-focus image fusion, since the shearlet transform can capture the detail information of images, an image fusion algorithm based on shearlet transform was proposed. Firstly, the shearlet transform was used to decompose the two registered original images, thus the low frequency sub-band coefficients and high frequency sub-band coefficients of different scales and directions were obtained. The fusion principle of low frequency sub-band coefficients was based on the method of weighted fusion, using the average gradient to calculate the weighted parameters in order to improve the edge fuzzy of the fused image. As for the high frequency sub-band coefficients, a fusion rule adopting the region variance combining with the region energy to get the detail information was presented. Finally, the fused image was reconstructed by inverse shearlet transform. The results show that the algorithm is superior to other fusion algorithms on subjective visual effect and objective evaluation.

Image fusion based on shearlet transform and region characteristics

1. College of Electronic and Information Engineering, Hebei University, Baoding 071002, China;

2. Key Laboratory of Hebei on Digital Medical Engineering, Hebei University, Baoding 071002, China

Received Date: 2014-01-14

Accepted Date: 2014-02-28

Available Online: 2015-01-25

Abstract: In order to improve the performance of multi-modality medical image fusion and multi-focus image fusion, since the shearlet transform can capture the detail information of images, an image fusion algorithm based on shearlet transform was proposed. Firstly, the shearlet transform was used to decompose the two registered original images, thus the low frequency sub-band coefficients and high frequency sub-band coefficients of different scales and directions were obtained. The fusion principle of low frequency sub-band coefficients was based on the method of weighted fusion, using the average gradient to calculate the weighted parameters in order to improve the edge fuzzy of the fused image. As for the high frequency sub-band coefficients, a fusion rule adopting the region variance combining with the region energy to get the detail information was presented. Finally, the fused image was reconstructed by inverse shearlet transform. The results show that the algorithm is superior to other fusion algorithms on subjective visual effect and objective evaluation.

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Reference (16)

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Image fusion based on shearlet transform and region characteristics

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