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

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] YoshizawaS, BelyaevA, YokotaH. Computer Graphics Forum, 2010, 29: 60

[2] LiY J, YanL, YangB. Open Automation and Control Systems Journal, 2015, 7: 275

[3] MairalJ, BachF, PonceJ, SapiroG, ZissermanANon-Local Sparse Models for Image RestorationIEEE International Conference on Computer Vision, 2009, 30: 2272

[4] DabovK, FoiA, KatkovnikVEgiazarian KarenIEEE Transactions on Image Processing, 2007, 16: 2080

[5] LIZ, LIUW-j, RONGM-t, LIUT-z. Information Technology, 2012, 4: 30

[6] DanielyanA, KatkovnikV, EgiazarianK. IEEE Transactions on Image Processing, 2012, 21: 1715

[7] DaiL, ZhangY, LiYInternational Journal of Signal ProcessingImage Processing and Pattern Recognition, 2013, 6: 41

[8] LuoX-G, LÜJ-R, WangH-J, YangQ. Journal of the University of Electronic Science and Technology of China, 2015, 44: 84

[9] ThaipanichT, OhB T, WuP-H, XuD, Kuo C.-CJ. IEEE Transactions on Consumer Electronics, 2010, 56: 2623

[10] WuY, DaiY, YinJ, WuJ. Transactions of Tianjin University, 2015, 21: 104

[11] Shreyamsha KumarB K. Signal, Image and Video Processing, 2013, 7: 1211

[12] GanK, TanJ, HeLNon-Local Means Image Denoising Algorithm Based on Edge Detection5th International Conference on Digital Home, 2014, 117

[13] GaoZ-l, YeW-l, ZhengC-t, WangY-d. Optoelectronics Letters, 2014, 10: 299

[14] ZhaoD-x, LiuP-j, ZhangD-g. Optoelectronics Letters, 2014, 10: 477

[15] KizilkayaA, ElbiM D. IETE Journal of Research, 2016, 62: 605

[16] IkemotoY, SekiyamaK. Journal of Ad vanced Computational Intelligence and Intelligent Informatics, 2016, 20: 705

[17] JonatasL d P, ClaudioF M T, HelioP. Applied Soft Computing, 2016, 46: 778