Abstract
Motion computation is an important part for image reflection separation methods using image sequence. As the motion of background and reflection is separated on image edges, in this paper we present a robust image reflection separation method based on sift-edge flow. Edge motion is firstly computed using sift-edge flow. Based on it, the sparse motion field of image edges is clustered into two parts and refined by RANSAC, which are then used to interpolate the dense motion fields of the background and reflection. The initial image decomposition is conducted by warping the input images to reference image using the dense motion fields of background and reflection respectively. Finally, with the initial solution provided, the background and reflection images can be separated using alternating optimization. Experiment results showed that our method can achieve a robust performance compared with the state of art.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Agrawal, A., Raskar, R., Nayar, S.K., Li, Y.: Removing photography artifacts using gradient projection and flash-exposure sampling. ACM Trans. Graph. (TOG) 24(3), 828–835 (2005)
Kong, N., Tai, Y.-W., Shin, J.S.: A physically-based approach to reflection separation: from physical modeling to constrained optimization. IEEE Trans. Pattern Anal. Mach. Intell. 36(2), 209–221 (2014)
Levin, A., Weiss, Y.: User assisted separation of reflections from a single image using a sparsity prior. IEEE Trans. Pattern Anal. Mach. Intell. 29(9), 1647–1654 (2007)
Li, Y., Brown, M.S.: Exploiting reflection change for automatic reflection removal. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 2432–2439 (2013)
Li, Y., Brown, M.S.: Single image layer separation using relative smoothness. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2752–2759 (2014)
Liu, C., Yuen, J., Torralba, A.: SIFT flow: dense correspondence across scenes and its applications. IEEE Trans. Pattern Anal. Mach. Intell. 33(5), 978–994 (2011)
Meer, P.: Robust techniques for computer vision. In: Emerging Topics in Computer Vision, pp. 107–190 (2004)
Rublee, E., Rabaud, V., Konolige, K., Bradski, G.: ORB: an efficient alternative to SIFT or SURF. In: 2011 IEEE International Conference on Computer Vision (ICCV), pp. 2564–2571. IEEE (2011)
Shih, Y., Krishnan, D., Durand, F., Freeman, W.T.: Reflection removal using ghosting cues. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3193–3201 (2015)
Simon, C., Park, I.K.: Reflection removal for in-vehicle black box videos. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 4231–4239 (2015)
Sinha, S.N., Kopf, J., Goesele, M., Scharstein, D., Szeliski, R.: Image-based rendering for scenes with reflections. ACM Trans. Graph. 31(4), 100:1–100:10 (2012)
Sun, C., Liu, S., Yang, T., Zeng, B., Wang, Z., Liu, G.: Automatic reflection removal using gradient intensity and motion cues. In: Proceedings of the 2016 ACM on Multimedia Conference, pp. 466–470. ACM (2016)
Szeliski, R., Avidan, S., Anandan, P.: Layer extraction from multiple images containing reflections and transparency. In: IEEE Conference on Computer Vision and Pattern Recognition, Proceedings, vol. 1, pp. 246–253. IEEE (2000)
Weinzaepfel, P., Revaud, J., Harchaoui, Z., Schmid, C.: DeepFlow: large displacement optical flow with deep matching. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1385–1392 (2013)
Xue, T., Rubinstein, M., Liu, C., Freeman, W.T.: A computational approach for obstruction-free photography. ACM Trans. Graph. (TOG) 34(4), 79:1–79:11 (2015)
Yang, J., Li, H., Dai, Y., Tan, R.T.: Robust optical flow estimation of double-layer images under transparency or reflection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1410–1419 (2016)
Acknowledgement
This paper is supported by the National Natural Science Foundation of China (No. 61572058) and the National High Technology Research and Development Program of China (No. 2015AA016402).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Du, S., Liang, X., Wang, X. (2018). A Robust Image Reflection Separation Method Based on Sift-Edge Flow. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_16
Download citation
DOI: https://doi.org/10.1007/978-3-319-77383-4_16
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-77382-7
Online ISBN: 978-3-319-77383-4
eBook Packages: Computer ScienceComputer Science (R0)