中国科学院机构知识库网格系统: Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE)

中国科学院机构知识库网格

Chinese Academy of Sciences Institutional Repositories Grid

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE)

文献类型：会议论文


作者	Wu Z.-G. ; Wang M.-J. ; Han G.-L.
出版日期	2011
会议名称	International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011
会议地点	Beijing, China
关键词	Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.
收录类别	EI
源URL	[http://ir.ciomp.ac.cn/handle/181722/33734]
专题	长春光学精密机械与物理研究所_中科院长春光机所知识产出_会议论文
推荐引用方式 GB/T 7714	Wu Z.-G.,Wang M.-J.,Han G.-L.. Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE)[C]. 见:International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011. Beijing, China.

入库方式： OAI收割

来源：长春光学精密机械与物理研究所

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