光电子快报(英文版), 2017, 13 (3): 237, Published Online: Sep. 13, 2018   

A novel denoising method for infrared image based on bilateral filtering and non-local means

Author Affiliations
Key Laboratory of Computer Vision and System, Ministry of Education of China, Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology, School of Computer and Communication Engineering, Tianjin University of Technology, Tianjin 300384, China
Abstract
This paper presents an image denoising method based on bilateral filtering and non-local means. The non-local region texture or structure of the image has the characteristics of repetition, which can be used to effectively preserve the edge and detail of the image. And compared with classical methods, bilateral filtering method has a better performance in denosing for the reason that the weight includes the geometric closeness factor and the intensity similarity factor. We combine the geometric closeness factor with the weight of non-local means, and construct a new weight. Experimental results show that the modified algorithm can achieve better performance. And it can protect the image detail and structure information better.
References

[1] Yoshizawa Shin, Belyaev Alexander and Yokota Hideo, Computer Graphics Forum 29, 60 (2010).

[2] Li Ying Jiang , Yan Li and Yang Bo, Open Automation and Control Systems Journal 7, 275 (2015).

[3] Mairal Julien, Bach Francis, Ponce Jean, Sapiro Guillermo and Zisserman Andrew, Non-Local Sparse Models for Image Restoration, IEEE International Conference on Computer Vision 30, 2272 (2009).

[4] Dabov Kostadin, Foi Alessandro, Katkovnik Vladimir and Egiazarian Karen, IEEE Transactions on Image Processing 16, 2080 (2007).

[5] LI Zheng, LIU Wen-jiang, RONG Meng-tian and LIU Tai-zhi, Information Technology 4, 30 (2012). (in Chinese)

[6] Danielyan Aram, Katkovnik Vladimir and Egiazarian Karen, IEEE Transactions on Image Processing 21, 1715 (2012).

[7] Dai Li, Zhang Yousai and Li Yuanjiang, International Journal of Signal Processing, Image Processing and Pattern Recognition 6, 41 (2013).

[8] Luo Xue-Gang, Lü Jun-Rui, Wang Hua-Jun and Yang Qiang, Journal of the University of Electronic Science and Technology of China 44, 84 (2015). (in Chinese)

[9] Thaipanich Tanaphol, Oh Byung Tae, Wu Ping-Hao, Xu Daru and Kuo C.-C. Jay, IEEE Transactions on Consumer Electronics 56, 2623 (2010).

[10] Wu Yiquan, Dai Yimian, Yin Jun and Wu Jiansheng, Transactions of Tianjin University 21, 104 (2015).

[11] B. K. Shreyamsha Kumar, Signal, Image and Video Processing 7, 1211 (2013).

[12] Gan Kaihua, Tan Jieqing and He Lei, Non-Local Means Image Denoising Algorithm Based on Edge Detection , 5th International Conference on Digital Home, 117 (2014).

[13] Gao Zong-li, Ye Wei-lin, Zheng Chuan-tao and Wang Yi-ding, Optoelectronics Letters 10, 299 (2014).

[14] Zhao De-xin, Liu Peng-jie and Zhang De-gan, Optoelectronics Letters 10, 477 (2014).

[15] Kizilkaya Aydin and Elbi Mehmet Dogan, IETE Journal of Research 62, 605 (2016).

[16] Ikemoto Yusuke and Sekiyama Kosuke, Journal of Ad vanced Computational Intelligence and Intelligent Informatics 20, 705 (2016).

[17] Jonatas Lopes de Paiva, Claudio F. M. Toledo and Helio Pedrini, Applied Soft Computing 46, 778 (2016).

LIU Feng-lian, SUN Meng-yao, CAI Wen-na. A novel denoising method for infrared image based on bilateral filtering and non-local means[J]. 光电子快报(英文版), 2017, 13(3): 237.

本文已被 3 篇论文引用
被引统计数据来源于中国光学期刊网
引用该论文: TXT   |   EndNote

相关论文

加载中...

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!