强激光与粒子束, 2015, 27 (1): 011012, 网络出版: 2015-01-26  

基于人工鱼群优化分块的多聚焦图像融合

Multi-focus images fusion based on block optimization using artificial fish-swarm algorithm
作者单位
1 电子科技大学 计算机学院, 成都 610054
2 电子科技大学 光电信息学院, 成都 610054
摘要
在多聚焦图像的融合过程中, 对源图像采用固定大小的分块会导致融合后的图像存在块效应、边缘模糊甚至聚焦错误。为了克服此问题, 提出了一种新的基于人工鱼群优化分块的多聚焦图像融合方法。首先, 将源图像分解成互不重叠的方块, 利用聚焦准则选取清晰度高的方块, 将已选择的方块合并重构成初始融合图像。然后, 利用改进的人工鱼群优化算法, 根据一定的适应度值, 寻找最优大小的分块方式, 获得更优的融合图像。 该方法与基于空域、频域及其他优化算法的融合方法进行了多个实验比较, 结果表明, 该方法获得的融合图像具有较好的客观质量和主观视觉感觉。
Abstract
The fixed block size of source images will result in blocking artifacts, fuzzy edge and focus error in multi-focus image fusion. To solve this problem, a new multi-focus image fusion algorithm based on block optimization using artificial fish-swarm is proposed. Firstly, the source images are decomposed into non-overlapping blocks and the sharper blocks are selected using a sharpness criterion. The selected blocks are combined to construct the initial fused image. Then, an improved artificial fish-swarm algorithm is used to optimize the block size according to a fitness function. The final fused image is obtained based on the best block size. Experimental results show that the proposed fusion method has a good quantitative evaluation and visual effect compared to other traditional methods.
参考文献

[1] Anish A, Jebaseeli T J. A Survey on multi-focus image fusion methods[J]. International Journal of Advanced Research in Computer Engineering & Technology, 2012, 1(8):319-324.

[2] 陈浩,朱娟,刘艳滢,等.利用脉冲耦合神经网络的图像融合[J].光学 精密工程, 2010, 18(4):995-1001.(Chen Hao, Zhu Juan, Liu Yanying, et al. Image fusion based on pulse coupled neural network. Optics and Precision Engineering, 2010, 18(4):995-1001)

[3] Mitianoudis N, Stathaki T. Pixel-based and region-based image fusion using ICA bases[J]. Information Fusion, 2007, 8(2):131-142.

[4] 晁锐,张科,李言俊.一种基于小波变换的图像融合算法[J].电子学报, 2004, 32(5):750-753.(Chao Rui, Zhang Ke, Li Yanjun. An image fusion algorithm using wavelet transform. Acta Electronica Sinica, 2004, 32(5):750-753)

[5] 孙巍,王珂,袁国良,等.基于复数小波域的多聚焦图像融合[J].中国图像图形学报, 2008, 13(5):951-957.(Sun Wei, Wang Ke, Yuan Guoliang, et al. A multi-focus fusion algorithm in the complex wavelet domain. Journal of Image and Graphics, 2008, 13(5):951-957)

[6] Nencini F, Garzelli A, Baronti S, et al. Remote sensing image fusion using the curvelet transform[J]. Information Fusion, 2007, 8(2):143-156.

[7] 屈小波,闫敬文,杨贵德.改进拉普拉斯能量和的尖锐频率局部化Contourlet域多聚焦图像融合方法[J].光学 精密工程, 2009, 17(5):1203-1212.(Qu Xiaobo, Yan Jingwen, Yang Guide. Multifocus image fusion method of sharp frequency localized contourlet transform domain based on sum-modified-Laplacian. Optics and Precision Engineering, 2009, 17(5):1203-1212)

[8] 焦竹青, 邵金涛, 徐保国.非下采样Contourlet变换域多聚焦图像融合方法[J].浙江大学学报, 2010, 44(7):1334-1337.(Jiao Zhuqing, Shao Jintao, Xu Baoguo. Novel multi-focus image fusion method in nonsubsampled contourlet transform domain. Journal of Zhejiang University, 2010,44(7):1334-1337)

[9] 张新曼,韩九强,王勇.一种遗传搜索块寻优的不同聚焦点图像融合算法[J].电子与信息学报, 2006, 28(11):2054-2057.(Zhang Xinman, Han Jiuqiang, Wang Yong. A multifocus image fusion algorithm for adaptive genetic search. Journal of Electronics and Information Technology, 2006, 28(11):2054-2057)

[10] 李爽, 林立宇, 陈荣元.基于粒子群优化算法的多聚焦图像融合[J].光电工程, 2009, 36(6):109-114.(Li Shuang, Lin Liyu, Chen Rongyuan. Multi-focus image fusion based on particle swarm optimization. Opto-Electronic Engineering, 2009, 36(6):109-114)

[11] Aslantas V, Kurban R. Fusion of multi-focus images using differential evolution algorithm[J]. Expert System with Application, 2010,37(12):8861-8870.

[12] 李晓磊,邵之江,钱积新.一种基于动物自治体的寻优模式:鱼群算法[J].系统工程理论与实践, 2002, 22(11):32-38.(Li Xiaolei, Shao Zhijiang, Qian Jixin. An optimizing method based on autonomous animats: Fish-swam algorithm. Systems Engineering Theory & Practice, 2002, 22(11):32-38)

[13] Fei C, Zhang P, Li J P. Motion estimation based on artificial fish-swarm in H.264/AVC coding[J]. WSEAS Transactions on Signal Processing, 2014, 10:221-229.

[14] Huang W, Jing Z. Evaluation of focus measures in multi-focus image fusion[J]. Pattern Recognition Letters, 2007, 28:493-500.

[15] Li S T, Kwok J T, Wang Y N. Combination of images with diverse focuses using the spatial frequency[J]. Information Fusion, 2001, 2(3):169-176.

[16] 林丹, 李敏强, 寇纪凇.进化规划和进化策略中变异算子的若干研究[J].天津大学学报, 2000, 33(5):627-630.(Lin Dan, Li Minqiang, Kou Jisong. On research of mutation operator in evolutionary programming and evolutionary strategies. Journal of Tianjin University, 2000, 33(5):627-630)

[17] 狄红卫,刘显峰.基于结构相似度的图像融合质量评价[J].光子学报, 2006, 35(5):766-771.(Di Hongwei, Liu Xianfeng. Image fusion quality assessment based on structural similarity. Acta Photonica Sinica, 2006, 35(5):766-771)

[18] Petrovic V, Xydeas C. Objective evaluation of signal-level image fusion performance[J]. Optical Engineering, 2005, 44:087003.

费春, 张萍, 李建平. 基于人工鱼群优化分块的多聚焦图像融合[J]. 强激光与粒子束, 2015, 27(1): 011012. Fei Chun, Zhang Ping, Li Jianping. Multi-focus images fusion based on block optimization using artificial fish-swarm algorithm[J]. High Power Laser and Particle Beams, 2015, 27(1): 011012.

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