计算机科学 ›› 2016, Vol. 43 ›› Issue (Z6): 122-124.doi: 10.11896/j.issn.1002-137X.2016.6A.029
王佺,聂仁灿,金鑫,周冬明,贺康建,余介夫
WANG Quan, NIE Ren-can, JIN Xin, ZHOU Dong-ming, HE Kang-jian and YU Jie-fu
摘要： 基于拉普拉斯金字塔(LP)与脉冲耦合神经网络(PCNN)变换,提出了一种有效的多聚焦图像融合算法。首先,利用拉普拉斯金字塔对图像进行对多尺度分解,并利用PCNN对每一尺度的分解图像进行处理,以获取描述特征聚类的神经元点火频率图；然后,利用点火频率图的局部拉普拉斯分量绝对和(SML),实现了图像每一尺度LP分解的融合；最后,通过LP分解的重构实现了对多聚焦图像的融合。实验结果表明,所提方法在各项客观评价指标上均优于传统融合算法,体现出了良好的性能。
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