Image fusion by pulse couple neural network with shearlet

Peng Geng; Zhengyou Wang; Zhigang ZhangZhong Xiao

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Image fusion by pulse couple neural network with shearlet

机译：Image fusion by pulse couple neural network with shearlet

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摘要

The shearlet representation forms a tight frame which decomposes a function into scales and directions, and is optimally sparse in representing images with edges. An image fusion method is proposed based on the shearlet transform. Firstly, transform the image A and image B by the shearlets. Secondly, a pulse couple neural network (PCNN) is used for the frequency subbands, which uses the number of output pulses from the PCNN's neurons to select fusion coefficients. Finally, an inverse shearlet transform is applied on the new fused coefficients to reconstruct the fused image. Some experiments are performed in images such as multi-focus images, multi-sensor images, medical images and multispectral images comparing the proposed algorithm with the wavelet, contourlet and nonsubsampled contourlet method based on the PCNN. The experimental results show that the proposed algorithm can not only extract more important visual information from source images, but also effectively avoid the introduction of artificial information. It significantly outperforms the traditional multiscale transform image fusion methods in terms of both visual quality and objective evaluation criteria such as MI and Q~(AB/F).

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来源
《Optical Engineering》 |2012年第6期|067005-1-067005-7|共7页
作者
Peng Geng; Zhengyou Wang; Zhigang ZhangZhong Xiao;
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作者单位

Shijiazhuang Tiedao University, School of Information Science and Technology, Shijiazhuang, 50043 China;

Shijiazhuang Tiedao University, Education Technology Center, Shijiazhuang, 050043 China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
image fusion; pulse couple neural network; shearlet transform; non-subsampled contourlet transform;

Image fusion by pulse couple neural network with shearlet

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