液晶与显示, 2015, 30 (2): 353, 网络出版: 2015-04-14  

FA-Criminisi快速图像修复

Fast Criminisi image inpainting based on firefly algorithm
作者单位
武汉科技大学 信息科学与工程学院, 湖北 武汉 430081
摘要
在经典Criminisi图像修复算法框架的基础上,针对优先权可靠性低和全局搜索最佳模板效率低、错误匹配率大的缺点进行改进.改进的算法为基于萤火虫算法(FA)的快速Criminisi图像修复算法.首先从数学的角度引入正规化函数至置信度,以此提升优先权计算的可靠性;然后引入FA到最佳模板的搜索与填充中,能够有效地将全局搜索与局部搜索有效地结合,鲁棒性较高,提高效率且错误匹配率低.实验结果表明:采用本文的改进算法能在保证修复质量的基础上降低时耗,提高效率.
Abstract
On the basis of Criminisi algorithmic framework,a fast Criminisi image inpainting based on firefly algorithm(FA) is proposed for the deficiencies of the priority and the best match template.Firstly,normalization function is introduced to the confidence to improve the reliability of the priority.Then,in order to improve and reduce error rate,FA which can combines global search and local search effectively is introduced to search the best template.Experimental results show that on the basis of guarantee the quality of image inpaiting,the improved algorithm can reduce the cost and improve efficiency.
参考文献

[1] Bertalmio M,Sapiro G,Caselles V,et al.Image inpainting[C].Proceedings of International Conference on Conputer Graphics and Interactive Techniques,USA:John Seely Brown,2000:417-424.

[2] 林云莉,赵俊红,朱学峰,等.基于图像分解的图像修复技术[J].计算机工程,2010,36(10):187-192.

    Lin Y L,Zhao J H,Zhu X F,et al.Image inpainting technology based on image decomposition[J].Computer Engineering,2010,36(10):187-192.(in Chinese)

[3] 朱文浩,魏国刚.基于样本的纹理合成[J].中国图形图像学报,2008,13(11):2063-2069.

    Zhu W H,Wei B G.The technology of sampled-based texture synthesis[J].Journal of Image and Graphics,2008,13(11):2063-2069.(in Chinese)

[4] Criminisi A,Perez P,Toyama K. Region filling and object removal by exemplar based inpainting[J].IEEE Trans Image Process,2004,13(9):1200-1212.

[5] 郭勇,王梅.基于改进样本块的数字图像修复算法研究[J].软件导刊,2013,12(10):156-158.

    Guo Y,Wang M.Research on exemplar based digital improving image inpainting algorithms[J].Software Guide,2013,12(10):156-158.(in Chinese)

[6] 常晨,尹立新,方宝龙.一种改进的Criminisi图像修复算法[J].计算机应用与软件,2012,29(9):238-267.

    Chang C,Yin L X,Fang B L. An improved Criminisi algorithm for image inpainting[J].Computer Applications and Software,2012,29(9):238-267.(in Chinese)

[7] 姚建亮,彭宏京.一种改进的基于样图的图像修复法[J].电子科技,2010,23(1):100-103.

    Yao J L,Peng H J.An improved exemplar-based method for image inpainting[J].Electronic Science and Technology,2010,23(1):100-103.(in Chinese)

[8] 刘洋,王昊京,田小建,等.采用区域分割的变尺寸样本块高效图像修复[J].光学精密工程,2010,18(12):2657-2664.

    Liu Y,Wang H J,Tian X J,et al.Efficient image inpainting based on region segmentation and varying exemplar[J].Optics and Precision Engineering,2010,18(12):2657-2664.(in Chinese)

[9] 刘长平,叶春明.一种新颖的仿生群智能优化算法:萤火虫算法术[J].计算机应用研究,2011,28(9):3295-3297.

    Liu C P,Ye C M.Novel bioinspired swarm intelligence optimization algorithm:firefly algorithm[J].Application Research of Computers,2011,28(9):3295-3297.(in Chinese)

李尊, 吴谨, 刘劲, 吴秋红. FA-Criminisi快速图像修复[J]. 液晶与显示, 2015, 30(2): 353. LI Zun, WU Jin, LIU Jin, WU Qiu-hong. Fast Criminisi image inpainting based on firefly algorithm[J]. Chinese Journal of Liquid Crystals and Displays, 2015, 30(2): 353.

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!