Abstract
In this study, we present a novel image fusion algorithm for multi-exposure dynamic images based on PatchMatch and illumination estimation. To eliminate the ghosting artifacts which often occur in the fusion results of existing exposure fusion methods when there are moving objects in the scenes, the fusion process of our proposed algorithm is as follows. First, we take advantage of the PatchMatch method to align the selected reference image with the other input images and then we fuse these images together based on illumination estimation to obtain the final fusion image. Experimental results demonstrate that our proposed method performs better than the existing fusion methods both in visual effect and objective indicators.
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References
Mertens T, Kautz J, Van Reeth F (2009) Exposure fusion: a simple and practical alternative to high dynamic range photography. In: Computer graphics forum, vol 28, no 1. Blackwell Publishing Ltd, pp 161–171
Shen R, Cheng I, Shi J et al (2011) Generalized random walks for fusion of multi-exposure images. IEEE Trans on Image Process 20(12):3634–3646
Song M, Tao D, Chen C et al (2012) Probabilistic exposure fusion. IEEE Trans Image Process 21(1):341–357
Zhang W, Cham WK (2012) Reference-guided exposure fusion in dynamic scenes. J Vis Commun Image Represent 23(3):467–475
Li S, Kang X (2012) Fast multi-exposure image fusion with median filter and recursive filter. IEEE Trans Consum Electron 58(2):626–632
Chapiro A, Cicconet M, Velho L (2011) Filter based deghosting for exposure fusion video. ACM SIGGRAPH 2011 Posters
Li Z, Zheng J, Zhu Z et al (2014) Selectively detail-enhanced fusion of differently exposed images with moving objects. IEEE Trans Image Process 23(10):4372–4382
Wu S, Xie S, Rahardja S et al (2010) A robust and fast anti-ghosting algorithm for high dynamic range imaging. In: Proceedings of 17th IEEE international conference on image processing (ICIP), pp 397–400
Hu J, Gallo O, Pulli K et al (2013) Hdr Deghosting: How to deal with saturation. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR)
Barnes C, Shechtman E, Goldman DB, Finkelstein A (2010) The generalized PatchMatch correspondence algorithm. In: ECCV
Vonikakis V, Bouzos O et al (2007) Multi-exposure image fusion based on illumination estimation. In: Proceedings of pacific graphics
Shaked D, Keshet R (2002) Robust recursive envelope operators for fast Retinex. Hewlett-Packard Research Laboratories Technical report
Acknowledgments
This work was supported by National Basic Research Program of China (973 Program) 2012CB821200 (2012CB821206) and the National Natural Science Foundation of China (No. 61320106006, No. 61532006, No. 61502042).
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© 2016 Springer Science+Business Media Singapore
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Fan, D., Du, J., Lee, J. (2016). Multi-exposure Dynamic Image Fusion Based on PatchMatch and Illumination Estimation. In: Jia, Y., Du, J., Zhang, W., Li, H. (eds) Proceedings of 2016 Chinese Intelligent Systems Conference. CISC 2016. Lecture Notes in Electrical Engineering, vol 404. Springer, Singapore. https://doi.org/10.1007/978-981-10-2338-5_45
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DOI: https://doi.org/10.1007/978-981-10-2338-5_45
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